Content of Figures
- Figure 1 The Overall Leadership rating for the Enterprise Databases in the Cloud market segment
- Figure 2 Product Leaders in the Enterprise Databases in the Cloud segment
- Figure 3 Innovation Leaders in the Enterprise Databases in the Cloud segment
- Figure 4 Market Leaders in the API Management and Security segment
- Figure 5 The Market / Product Matrix
- Figure 6 The Product / Innovation Matrix
- Figure 7 The Innovation/Market Matrix
As businesses continue embracing the cloud to achieve better agility and innovation, lower the time to market for their digital services, and eliminate the costs of maintaining their own infrastructures, more and more corporate data migrates to the cloud as well. These developments do not just affect traditional enterprise workloads but cover a broad range of new use cases like IoT telemetry collection, business intelligence, or security analytics.
Market trends indicate that companies are increasingly developing cloud-first strategies for their data management, even when facing additional compliance regulations. Scalability, flexibility, range of services and predictable costs – these are the primary factors for the growing adoption of managed database services in the cloud.
Nowadays, most sufficiently complex cloud migration projects or even cloud-native applications inevitably end up using multiple types of databases and other data stores for structured and unstructured information depending on their business requirements. Recently introduced data protection regulations like the European Union’s GDPR or California’s CCPA make no distinction between relational databases, data lakes, or file stores – all data is equally sensitive regardless of the underlying technology stack.
Thus, in this KuppingerCole Leadership Compass, we are focusing primarily not on the technical capabilities of individual database management solutions that can be optionally deployed on a cloud infrastructure. Rather, we want to focus on vendors that offer comprehensive business-focused solution portfolios that cover a broad range of use cases, whether this functional scope is supported by a single universal database engine or a vendor offers a choice of individual products to choose from. We also consider solutions outside of the traditional definition of a database management system, provided that they address a relevant business requirement for storing, managing, and processing data in the cloud.
Here are some of the solutions that we consider relevant for this Leadership Compass:
- Traditional enterprise DBMS offered as managed services in the cloud
- Cloud-based Big Data platforms for large-scale analytic workloads
- Vendors or service providers offering comprehensive suites of independent database engines for various usage scenarios: relational, document, graph, key-value, and other types under unified management
- In-memory databases and computing platforms or similar technologies
- Other innovative data management products with a strong cloud-first focus.
1.1 Market Segment
Databases are arguably still the most widespread technology for storing and managing business-critical digital information. Sensitive financial transactions, confidential customer records, sensor data from IoT devices, or just some other kind of business-relevant information – whether on-premises or in the cloud, they end up stored in a database for management, archival, analytics, or any other kind of processing. However, with the growing adoption of modern, cloud-native application architectures and simply because of the increased volumes and complexity of information that ends up being stored in the cloud, enterprise applications can no longer rely on a single type of database to address the broad range of requirements. For example, developers might opt for a specialized time-series database to record sensor data from IoT devices, store collected information in a data lake to simplify analytics but rely on a distributed NoSQL database engine to power their client application.
In fact, it would not be an overstatement to say that the very definition of “database” for many organizations is radically changing. Nowadays, a cloud-native enterprise IT project simply cannot stick to traditional monolithic designs. Instead, loosely coupled distributed architectures like microservices are preferred. Applications that are deployed across multiple cloud regions or even multiple clouds are a norm. These modern architectures introduce new requirements for database management systems.
Developers expect databases to be cloud-native as well: able to support highly distributed and scalable deployments, withstand planned and unplanned outages, accommodate multiple different data models while still allowing to access analyze data across them with low latency, and, last but not least, implement reliable and compliant data protection and threat mitigation controls. Ideally, a modern enterprise database should be completely managed by a third party, allowing customers to focus on application logic instead of infrastructure operations and maintenance. In a way, an ideal enterprise cloud-native database is the one that does not expose any of its underlying infrastructure: a serverless database for serverless computing.
Unfortunately, such a dream database solution that would universally fit all potential cloud-native use cases probably does not exist yet. Still, a market for enterprise databases in the cloud is quite substantial and will definitely continue to grow and evolve, since the demand for such solutions is immense. Whether a particular vendor can address such a broad range of business requirements with a single integrated service or provides a selection of specialized services in a suite is not the primary focus of our analysis: instead, we are looking at the overall ability of a vendor to support a potential customer in as many use cases as possible.
In this report, these are the key areas we were looking for:
- Solutions that provide enterprise-level data management capabilities for various usage scenarios
- Solutions which are offered as managed services within a single or multiple cloud environments
- Solutions that take advantage of the core capabilities of cloud services: scalability and performance, managed or automated patching, tuning, and optimization, etc.
- Solutions that implement the necessary data protection and compliance controls to prevent data breaches and violations of government or industry regulations
- Solutions that provide comprehensive centralized management, monitoring and analytics capabilities integrated with other cloud services, vendor’s own or third-party ones.
This Leadership Compass is one of the first KuppingerCole’s reports investigating this approach towards market analysis. This means that several notable vendors were unable to participate in our rating for various reasons – they will still be mentioned in the later chapter “Vendors to watch”. Still, even the relatively small selection of companies we do have in the main rating demonstrates a broad variety of approaches companies are utilizing to address the customer requirements for a truly universal cloud database service.
We have a mix of traditional database vendors like Oracle, which work hard to elevate their decades-long database expertise to the cloud scale; veteran cloud service providers like AWS that strive to offer their customers a broad selection of specialized database engines; and, of course, young innovative companies like MongoDB that had to start from scratch to design their products to be truly cloud- and even multi-cloud-native. We even have a couple of vendors that don’t offer their own database services but help make database operations and data management in the cloud more efficient and secure.
1.2 Delivery models
Since this report focuses on enterprise databases in the cloud, we are explicitly excluding products that are primarily delivered for on-premises use and only support optional IaaS-based cloud deployment. For example, we would not consider “vanilla” PostgreSQL for inclusion, yet quite a few vendors do offer cloud-based managed database services implemented using PostgreSQL technology.
We are also not including solutions that only address a small subset of database management capabilities (for example, only a key-value database service) unless they are offered as a part of a broader portfolio. Finally, we are not covering additional tools and capabilities such as data migration or analytics, unless they are provided as an integral part of a data management service.
Thus, native support for cloud deployments is the primary criterion for inclusion in this Leadership compass; support for multi-cloud and hybrid deployment scenarios is also considered a major advantage. Also, here are some features and criteria that directly and positively influence a solution’s rating in our evaluation:
- Integrated protection controls for data integrity and confidentiality (including but not limited to encryption and masking, segregation of duty, and user behavior monitoring). Please note that KuppingerCole has a separate Leadership Compass devoted entirely to the topic of Database and Big Data security. Still, data protection and compliance features are one of the required capabilities for this rating as well.
- Minimized downtime for maintenance, as well as resilience against unplanned downtime. This is one of the crucial yet often overlooked criteria for selecting a cloud database capable of providing the highest availability for business-critical applications: remember that planned downtime is often not included in a service level agreement.
- Compatibility with existing on-premises database management solutions, as well as other means to simplify migration of existing data and workloads to the cloud. By relying on a consistent set of supported APIs and protocols across on-premises and cloud databases, application developers can not only dramatically reduce the time to market for their apps, but also minimize the danger of vendor lock-in when using proprietary interfaces.
1.3 Required Capabilities
When evaluating the products, besides looking at the aspects of
- overall functionality
- size of the company
- number of customers
- number of developers
- partner ecosystem
- licensing models
- platform support
we also considered the following key functional areas of database platforms in the cloud:
- Supported Data Models – we expect an enterprise-class cloud database service to support multiple data models beyond the traditional relational databases. These might include multiple types of “NoSQL” data models like key-value, graph, or document databases as well as more specialized database types like time-series databases or even centralized and distributed ledgers.
- Integrated Management – whether a vendor offers a universal multi-model database engine or many specialized database services, we still expect it to provide unified management and monitoring, as well as a consistent approach towards relieving the customers from managing the underlying infrastructure.
- Database and Data Security – an enterprise-class database service must implement a comprehensive set of data protection capabilities, fine-grained access controls, activity monitoring, audit, and compliance features as well as offer comprehensive multi-layered protection against external and internal threats.
- Data Management and ETL – here we evaluate the capabilities and services offered by the vendor to enable migration of existing data and applications to the cloud, integration with external data sources, as well as managed extract, transform and load capabilities.
- Business Analytics – although we do not expect every cloud database service to offer its own business analytics solutions, making the data in the cloud available for 3rd party analytics tools at scale is a crucial capability. This covers such functionality as managed data warehouses and data lakes, as well as optional AI/ML technology integrations.
- IoT and Real-Time Processing – capturing streams of data in real-time is an increasingly popular use case for cloud applications, especially relevant for large fleets of IoT sensors, but also financial transactions, event streams, or security intelligence. Support for reliable and secure data streaming with real-time analytics is another crucial enterprise cloud database capability.
- DevOps and Integration – this includes providing a broad set of tools and integrations for developers to support CI/CD pipelines, enabling full information lifecycle management including proper disposal of test data as well as supporting DataOps methodology with technologies like data virtualization and self-service functions for developers, data scientists, and other data consumers.
- Deployment and Scalability – while not a functional capability per se, it is a critical requirement for all cloud-native database services to be able to withstand high loads, support scaling without any significant limitations and support deployments in high availability configurations. Databases specifically designed with modern highly distributed application architectures in mind will receive high ratings here as well.
Selecting a vendor of a product or service must not be only based on the comparison provided by a KuppingerCole Leadership Compass. The Leadership Compass provides a comparison based on standardized criteria and can help to identify vendors that shall be further evaluated. However, a thorough selection includes a subsequent detailed analysis and a Proof of Concept of the pilot phase, based on the specific criteria of the customer.
Based on our rating, we created the various Leadership ratings. The Overall Leadership rating provides a combined view of the ratings for
- Product Leadership
- Innovation Leadership
- Market Leadership
2.1 Overall Leadership
The Overall Leadership rating is a combined view of the three leadership categories: Product Leadership, Innovation Leadership, and Market Leadership. This consolidated view provides an overall impression of our rating of the vendor’s offerings in this market segment. Notably, some vendors that benefit from a strong market presence may slightly drop in other areas such as innovation, while others show their strength, in the Product Leadership and Innovation Leadership, while having a relatively low market share or lacking a global presence.
Therefore, we strongly recommend looking at all leadership categories, the individual analysis of the vendors, and their products to get a comprehensive understanding of the players in this market.
The distribution of overall leaders across the rating axis is not at all surprising: the Leaders segment is mostly dominated by large cloud service providers like AWS, IBM, Microsoft, and Oracle, with each capable of offering a broad and comprehensive portfolio of database-related services for their customers. It is interesting to observe how two of the leaders represent different approaches towards the design of their database service portfolios.
Oracle, a database vendor with decades of expertise in this field, is a relative newcomer to the cloud market, but even in the cloud, its approach is focused on offering a single multi-model converged database engine to address as many use cases as possible while enabling unified data management and analytics. Oracle database is an enterprise DBMS in the traditional sense, yet the complexity of its management and maintenance is completely hidden from customers with the company’s autonomous cloud services, making it accessible even to small businesses or individual developers.
AWS is the oldest and arguably still the largest cloud service provider in terms of its infrastructure footprint; it has started offering databases in the cloud in 2009. Currently, the company has a portfolio of 15 specialized fully managed database services, many of which are based on popular open-source database engines, ensuring that their customers can always choose the most fitting tool for their requirements.
Both of these strategies have their advantages and shortcomings, but at KuppingerCole, we believe that the unified approach offers more long-term benefits for customers, including significantly lower learning curve for developers, more flexibility in changing data models mid-development, and availability of all project data in one place without creating multiple data siloes. A major downside of the other, tool-focused approach is, of course, the increased difficulty of consistent data management and analytics across several incompatible database engines, which has to be compensated with additional tools or services.
The only other company with a completely different market approach among the leaders is MongoDB: although the company does not operate its own cloud infrastructure, its flagship cloud database solution is available on all major public clouds.
The challenger segment is populated by companies like Delphix and Nutanix, which do not produce any database engines themselves. However, both vendors offer innovative solution platforms that can greatly improve the operational efficiency of existing databases in the cloud and thus we consider them just as relevant for our Leadership Compass. Finally, Couchbase is an innovative database (also offered as a service) designed for unlimited scalability and globally distributed deployment scenarios.
No vendors appear in the Follower segment of our overall rating.
Unfortunately, several other major players in this market were unable to participate in this rating: you will find them mentioned in a later chapter “Vendors to watch”.
Overall Leaders are (in alphabetical order):
2.2 Product Leadership
The first of the three specific Leadership ratings is about Product Leadership. This view is mainly based on the analysis of product/service features and the overall capabilities of the various products/services.
In the Product Leadership rating, we look specifically for the functional strength of the vendors’ solutions, regardless of their current ability to grab a substantial market share.
As mentioned earlier, our rating includes companies that represent completely different approaches towards designing their cloud database service portfolios. Still, even though it might be somewhat difficult to directly compare apples to oranges (or, in this case, large cloud service providers with multiple projects to small and focused startup companies), this report focuses less on individual product capabilities and more on the overall benefits of a particular vendor’s offering for your current or future cloud-native project.
We would like to stress once again that depending on your company’s specific functional requirements, scope and scale of your project, data models involved, even security and compliance regulations that apply to you, a specific vendor might be a better fit even if it has a lower product rating in this chapter.
In our Product Leadership, we can observe two clear leaders: Oracle and AWS. Both are veteran vendors and undisputed experts in their core competencies (cloud infrastructure for AWS and database development for Oracle). Both offer broad portfolios of database-related products and services, powered by robust cloud infrastructures and comprehensive security and compliance controls. However, as mentioned earlier, the companies represent very different approaches toward addressing customer use cases.
Microsoft and IBM are also found among the product leaders: both combine their own traditional relational database technologies with 3rd party NoSQL database services hosted in their cloud infrastructures.
Finally, MongoDB is also recognized as a product leader with its cloud-agnostic NoSQL database product, which is now also offered as a managed cloud service on major cloud platforms. As one of the most popular NoSQL database engines, MongoDB offers maximum deployment flexibility and an interface for developers so familiar that other vendors chose to implement the MongoDB protocol for their own databases.
Nutanix, Delphix, and Couchbase are found in the Challenger segment, owing largely to a relatively narrow functional focus of their products. Nutanix with its Era platform automates and simplifies database provisioning, administration, and protection, helping enterprises to drive efficiency, agility, cost-effectiveness, and scalability across their enterprise applications. Delphix offers a platform for data virtualization to accelerate cloud migration, automate development pipelines, and ensure regulatory compliance in the cloud. Couchbase offers a multi-model document-oriented database designed for massive scalability and business-critical applications.
There are no Followers in our Product Leadership rating.
Product Leaders are (in alphabetical order):
2.3 Innovation Leadership
Another angle we take when evaluating products/services concerns innovation. Innovation is, from our perspective, a key capability in IT market segments. Innovation is what customers require for keeping up with the constant evolution and emerging customer requirements they are facing.
Innovation is not limited to delivering a constant flow of new releases but focuses on a customer-oriented upgrade approach, ensuring compatibility with earlier versions especially at the API level, and on supporting leading-edge new features that deliver emerging customer requirements.
When comparing the degree of innovation among vendors as diverse as we have in our rating, it is again not as easy to properly quantify their contributions to the overall development of the cloud database market. Each of the companies represented here invests a lot of effort into new innovative features and capabilities of their products, but since we’re focusing more on customer experience in this report, some of those developments were considered more impactful.
Oracle has been continuously developing numerous innovative database capabilities for decades, but since its foray into the cloud market, the company’s been focusing on delivering its database expertise as fully managed cloud services. Having all capabilities available in a single multi-model converged database engine running on a highly optimized hardware platform powered by intelligent automation eliminating the human factor from database management – this is the kind of innovation customers are looking for in a cloud database.
MongoDB has been one of the most popular NoSQL databases for years and listening to its customers and delivering a constant stream of new capabilities is one of the major reasons for this. MongoDB Atlas, a fully managed offering on all major public clouds, has been available since 2016. Recent innovations have expanded beyond the transactional database with search, data lake, and mobile support. Multiple scalability, performance, and security enhancements in the latest release are worth noting as well.
Both AWS and Microsoft, as leading cloud service providers, offer multiple managed database services as a part of their cloud service portfolios. Their approach is to provide an optimized and convenient solution for every customer use case imaginable: numerous database engines, cloud migration services, integrations with IoT infrastructures, security and compliance monitoring, and numerous other useful tools.
Couchbase, Delphix, and IBM can be found in the Challengers segment. This placement does not discriminate the scope of innovations these vendors deliver to their customers; rather, it reflects a more specialized focus and more technical nature of these developments.
There are no Followers in this Innovation Leadership rating.
Innovation Leaders are (in alphabetical order):
2.4 Market Leadership
Here we look at Market Leadership qualities based on certain market criteria including but not limited to the number of customers, the partner ecosystem, the global reach, and the nature of the response to factors affecting the market outlook. Market Leadership, from our point of view, requires global reach as well as consistent sales and service support with the successful execution of marketing strategy.
Please note that this rating does not reflect the overall market presence of large vendors, but only limited to the market shares of their respective managed cloud database services. Unsurprisingly, AWS and Microsoft, as the largest players in the overall public cloud industry, occupy top positions in our market leadership rating. Both dominate the market both in terms of the numbers of customers as well as database-related revenue.
Although Oracle has arguably the largest number of on-prem database customers, by far not all of them have already decided to migrate to the Oracle Cloud. Thus, Oracle occupies the third position in market leadership, followed by MongoDB, which dominates the NoSQL database market across all major cloud platforms.
IBM and Nutanix, while both large companies with a strong overall market presence, have somewhat lower penetration of the cloud database market, not to mention Couchbase and Delphix, which are substantially smaller. All four can be found in the Challenger segment of our market leadership rating.
Still, there are no followers in this rating as well.
Market Leaders are (in alphabetical order):
3 Correlated View
While the Leadership charts identify leading vendors in certain categories, many customers are looking not only for, say, a product leader but for a vendor that is delivering a solution that is both feature-rich and continuously improved, which would be indicated by a strong position in both the Product Leadership ranking and the Innovation Leadership ranking.
Therefore, we deliver additional analysis that correlates various Leadership categories and delivers an additional level of information and insight. These allow identifying, for instance, highly innovative but specialized vendors or local players that provide strong product features but do not have a global presence and large customer base yet.
3.1 The Market/Product Matrix
The first of these correlated views looks at Product Leadership and Market Leadership.
Here one can identify which vendors are better positioned in our analysis of Product Leadership compared to their position in the Market Leadership analysis. Vendors above the line are sort of “overperforming” in the market. It comes as no surprise that these are mainly the very large vendors, while vendors below the line are often innovative but focused on specific regions.
Unsurprisingly, we find the three large cloud service providers, AWS, Microsoft, and Oracle, in the Market Champions segment. Joining them in the same quadrant is MongoDB, a leading NoSQL solution provider whose managed cloud offering is also excellent. Oracle’s position below the axis indicates that it is currently still somewhat underperforming in the cloud database market, showing potential for future growth.
IBM can be found in the middle right-hand box, indicating strong functional capabilities not matched by an equally large market presence. This is somewhat surprising given the strong role Db2 plays for IBM’s strategic cloud services such as AI technologies and security analytics.
The rest of the companies can be found in the central segment close to the axis, indicating a substantial, balanced position appropriate for their more specialized solutions.
3.2 The Product/Innovation Matrix
The second view shows how Product Leadership and Innovation Leadership are correlated. Vendors below the line are more innovative, vendors above the line are, compared to the current Product Leadership positioning, less innovative.
Here, we see a rather low correlation between the product and innovation ratings, with many vendors being far from the dotted line. This is a strong indicator of a market segment that is far from mature and established phase and the tendency of various vendors to offer different solutions for similar customer requirements. It also highlights the overall complexity of comparing solutions focused on different functional areas against each other.
On the graph we again observe the same four major vendors in the Technology Leaders segment: AWS, Microsoft, and Oracle joined by MongoDB. Just like the previous graph, this reflects their overall strength and ability to continuously deliver new innovative features in their products.
IBM is placed in the top middle box, indicating a functionally capable and robust, but somewhat less innovative database solution, which again reflects the company’s strategic focus not primarily in this market segment.
Nutanix, on the other hand, has landed in the right middle segment, indicating the opposite: a stronger innovation drive that has not yet matured enough into a broad set of functional capabilities. This is also unsurprising since Nutanix Era is a relatively young offering from the company, launched just 2 years ago.
Couchbase and Delphix again occupy the middle segment, showing a good balance of innovation and functionality within their respective focus area.
3.3 The Innovation/Market Matrix
The third matrix shows how Innovation Leadership and Market Leadership are related. Some vendors might perform well in the market without being Innovation Leaders. This might impose a risk to their future position in the market, depending on how they improve their Innovation Leadership position. On the other hand, highly innovative vendors have a good chance of improving their market position but often face risks of failure, especially in the case of vendors lacking a strong strategic vision.
Vendors above the line are performing well in the market compared to their position in the Innovation Leadership rating. This includes AWS, IBM, and Microsoft – large veteran enterprises with a long history and mature portfolios.
Vendors below the line show, based on their ability to innovate, the biggest potential for improving their market position. These include both smaller, more disruptive companies like Couchbase and Delphix, as well as Oracle, which is currently undergoing a major transformation from a database technology vendor to a major player in the cloud service market. MongoDB and Nutanix, sized in between these groups and growing quickly, are also innovating beyond their traditional areas of expertise.
Again, completely unsurprisingly, the same four vendors (AWS, Microsoft, MongoDB, Oracle) are present in the “Big Ones” segment.
Nutanix has landed in the middle right box, indicating a somewhat lower market presence as expected for its innovativeness. Couchbase, Delphix, and IBM occupy the middle segment, indicating their Challenger status both in market and innovation leadership.
4 Products and Vendors at a glance
This section provides an overview of the various products we have analyzed within this KuppingerCole Leadership Compass document. This overview goes into detail on the various aspects we include in our ratings, such as security, overall functionality, and so on.
It provides a more granular perspective, beyond the Leadership ratings such as Product Leadership, and allows identifying in which areas vendors and their offerings score stronger or weaker. Details on the rating categories and scale are listed in chapter 7.2 to 7.4. Based on our evaluation, a comparative overview of the ratings of all the products covered in this document is shown in the table below.
|Delphix Dynamic Data Platform|
|IBM Cloud Db2|
Besides, we provide four additional ratings for the vendors. These go beyond the product view provided in the previous section. While the rating for Financial Strength applies to the vendor, the other ratings apply to the product.
|Vendor||Innovativeness||Market Position||Financial Strength||Ecosystem||Legend:|
|Amazon Web Services|
5 Product/Vendor Evaluation
This section contains a quick one-page rating for every enterprise cloud database offering we’ve included in this Leadership Compass. For some of the products and services mentioned in this chapter, there are additional KuppingerCole Reports available, providing more detailed information.
Please note that in this report we are focusing less on the capabilities of standalone products or services and more on the overall ability of a vendor to deliver integrated, scalable, secure, and convenient solutions for their customers’ cloud projects. Thus, these reviews represent KuppingerCole’s assessment of vendors’ whole portfolios of managed database products or services, which for some companies might incorporate dozens of individual tools.
In addition to the ratings for our standard categories such as Product Leadership and Innovation Leadership, we add a spider chart for every vendor we rate, looking at specific capabilities for the market segment researched in the respective Leadership Compass. The spider graphs provide comparative information by showing the areas where vendor services are stronger or weaker. Some vendor services may have gaps in certain areas while being strong in other areas. These kinds of solutions might still be a good fit if only specific features are required. Other solutions deliver strong capabilities across all areas, typically by combining several various services into suites or integrated platforms.
This report focuses on the following eight categories:
- Supported Data Models – we expect an enterprise-class cloud database service to support multiple data models beyond the traditional relational databases.
- Integrated Management – unified management and monitoring, as well as a consistent approach towards relieving customers from managing the underlying infrastructure.
- Database and Data Security – data protection capabilities, fine-grained access controls, activity monitoring, audit, and compliance features as well as protection against external and internal threats.
- Data Management and ETL – migration of existing data and applications to the cloud, integration with external data sources, as well as managed extract, transform, and load capabilities.
- Business Analytics – making the data in the cloud available for analytics tools at scale, across heterogeneous data sources.
- IoT and Real-Time Processing – support for reliable and secure data streaming with real-time analytics.
- DevOps and Integration –CI/CD pipeline integration, information lifecycle management, data virtualization, and self-service functions for developers, data scientists, and other data consumers.
- Deployment and Scalability – ability to withstand high loads, support scaling without any significant limitations, and implement deployments in high availability configurations.
5.1 Amazon Web Services
Amazon Web Services, Inc. (AWS) is a multinational cloud service provider headquartered in Seattle, USA. A subsidiary of the American retail giant Amazon.com, AWS was initially formed to consolidate and standardize the computing infrastructure powering Amazon’s online business. In 2006, the AWS platform was launched officially with the vision of offering on-demand access to this infrastructure to customers on a subscription basis, thus essentially making the company the first major player of the cloud computing market.
AWS offers a broad and versatile portfolio of database services for any kind of customer – from small open source projects to business-critical enterprise. AWS makes a strong focus on providing purpose-built database engines for different data models and diverse use cases. Besides being able to provide cloud infrastructure for just about any existing database, the company offers 15 fully managed database services, including relational (Amazon Aurora and Amazon RDS), key-value (Amazon DynamoDB), document (Amazon DocumentDB), in-memory (Amazon ElastiCache), graph (Amazon Neptune), time-series (Amazon Timestream), and ledger (Amazon QLDB) databases.
Breaking away from traditional monolithic database engines that inhibit elastic scalability and allowing customers to select the most suitable product to address a specific problem is the primary focus of the company’s database portfolio strategy. A combination of highly optimized infrastructure, self-healing storage, and serverless architecture of database services allows AWS to offer a 3 to 5 times performance increase compared to similar database engines deployed elsewhere.
A number of database services offered by AWS are either implemented on top of popular open-source engines like MySQL and PostgreSQL or offer protocol-level compatibility with them, like Amazon DocumentDB with MongoDB compatibility. AWS also offers managed MySQL and Oracle databases to its users. This allows the company to claim up to 10x cost reduction compared to traditional enterprise databases by eliminating the licensing costs.
Eight of AWS’s databases share an SQL dialect which shortens the learning curve when a customer decides to switch to an AWS cloud database. Furthermore, given the broad customer base, the provider offers tailored use cases that customers can look at before making the initial choice for a database. Naturally, the company offers comprehensive database migration services as well.
True to its overall strategy, AWS strives to offer its customers the most capable specialized and performance-optimized tools for various cloud-native and hybrid projects at a very competitive price. If you look for a tailored solution to a specific use case, the AWS database service portfolio might be the ideal solution for you.
Couchbase is a privately held database technology vendor headquartered in Santa Clara, California. Created in 2011 as a merger of teams behind two popular open-source database projects, the company has developed an enterprise-class, multicloud to edge database designed for business-critical applications on a massively scalable platform. Combining the modern capabilities of many NoSQL databases with a familiar SQL interface, Couchbase is specifically targeted at enterprise customers transitioning from legacy on-prem databases to a fully managed database-as-a-service.
Designed from the ground up as a masterless, clustered, and replicated distributed database, Couchbase provides a single robust platform for massively scalable cloud-native projects, seamlessly spanning across multiple clouds, on-prem deployments, and even embedded edge devices. On top of this elastic, asynchronous architecture, the solution offers a rich service layer with functions like SQL-based querying, indexing, full-text search, eventing, analytics, mobile replication, and so on.
Although Couchbase was available as self-managed software for years, the company has recently introduced several new managed deployment options. These include Couchbase Autonomous Operator, which automates deployment and management of the database in Kubernetes container orchestration environments managed by the customer, and Couchbase Cloud – a fully-managed DBaaS service that combines a control plane managed by Couchbase with a data plane deployed on customer’s private or VPC infrastructure. Both solutions are infrastructure-agnostic, multicluster-aware, and support seamless multi-cloud deployments that respect geographically driven data sovereignty regulations like GDPR. Common Couchbase applications such as user profile management can also be designed to support data ownership regulations like CCPA.
Although Couchbase is technically a traditional NoSQL database with a memory-first key-value and document model, it implements an SQL-compatible N1QL query language, which simplifies migrations from relational databases and lowers the learning curve for developers. Couchbase’s MPP-powered analytics service eliminates the need to dump data to warehouses or lakes for real-time analysis, while Its eventing service allows it to provide data-driven change instructions to applications. It also supports distributed, multi-document ACID transactions and with sub-millisecond latencies and high availability is suitable for the most critical system-of-record applications.
Additionally, Couchbase provides offline-first mobile and edge computing extensions which allow customers to develop innovative peer-to-peer synchronization applications for a broad range of mobile and smart device platforms.
Even though Couchbase does not aim to fully replace existing enterprise RDBMS, it does help many customers with migrating on-prem and legacy applications to the cloud by caching and distributing data for modern cloud-native architectures, while keeping a legacy system of records in a relational database. With a familiar SQL-like interface, practically unlimited scalability, seamless multi-cloud and hybrid support, and a fully managed control plane, Couchbase might be a compelling choice for companies that want to migrate their critical applications to the cloud at their own pace.
Delphix is a privately held software development company headquartered in Redwood City, California, USA. It was founded in 2008 with a vision of a dynamic platform for data operators and data consumers within an enterprise to collaborate in a fast, flexible, and secure way. With offices across the USA, Europe, Latin America, and Asia, Delphix is currently serving over 300 global enterprise customers including 30% of the Fortune 100 companies.
The company provides a compelling alternative to the complex and tedious process of migrating on-premises databases to the cloud: data virtualization. The original data remains in place, but the platform provides a virtual copy in the cloud that appears and behaves like a local database instance. Using various optimization methods, such a platform can quickly and efficiently create multiple virtual copies of the same data, which are portable, transparent, and, if needed, writable as well. Combined with self-service capabilities and API-driven automation functions, they ensure that data consumers can get access to the data they need as quickly and efficiently as possible.
Delphix Dynamic Data Platform is an integrated and fully automated DataOps platform that combines data virtualization and data masking, making corporate data from various sources available across on-premises and cloud environments quickly and securely at the speed and scale needed to support a wide range of use cases: from development and testing to data analytics to cloud migration to disaster recovery. Using the integrated data masking technology, Delphix implements the automatic discovery of sensitive data and its obfuscation by using masking or reversible tokenization as a seamless part of the virtualization process.
Flexible deployment options and a wide range of supported databases and file systems make the Delphix platform a very interesting choice for companies that are planning a deep dive into the DataOps methodology or just looking for a universal tool to address multiple pain points in such areas as DevOps, data analytics, cloud migration, and even disaster recovery. The company provides pre-configured images for deployment on AWS, Azure, and GCP public clouds, and several cloud-based database types are supported as well. Thus, the platform enables transparent data virtualization across hybrid environments, substantially reducing the amount of data that must be replicated into the cloud and automatically enforcing the security and compliance policies.
IBM Corporation is a multinational technology and consulting company headquartered in Armonk, New York, USA. With over 100 years of history, IBM has evolved from a computing hardware manufacturer towards offering a broad range of software solutions and infrastructure, hosting, and consulting services in such high-value markets as business intelligence, data analytics, cloud computing, virtualization, and information security.
The foundation of IBM Cloud’s database portfolio is IBM Db2, the company’s relational database (or rather, a family of data management products). Designed for advanced data management and analytics capabilities for transactional workloads, Db2 has been on the market for nearly 30 years. With time, it has evolved to incorporate object-relational features and non-relational data models like JSON and XML. Db2 Warehouse is an analytics data warehouse that supports multiple data types and analytics engines with multi-parallel processing and in-memory performance.
Db2 on Cloud is IBM’s fully managed cloud database offering, which can be deployed both on IBM Cloud and AWS. Compared to traditional deployments, the solution offers such key benefits as elastic and independent compute and storage scaling, high availability disaster recovery (HADR) architecture enabling scaling and patching without downtime, as well as security features like encryption and private networking. A notable feature of Db2 on Cloud is data federation: data distributed over multiple on-prem and cloud-based databases and warehouses can be accessed with a single query; this works even for multiple database types including Oracle, SQL Server, and PostgreSQL.
In the recent releases, IBM has substantially expanded the AI capabilities of the database. Machine learning methods are now used to tune workloads and optimize queries for improved performance. The included Augmented Data Explorer provides an analytics portal that allows users to explore their data and generate statistical insights using graphs and natural language instead of complex queries. New tools for developers and data scientists help them generate value from their data much faster.
Notably, IBM has shifted its marketing focus recently from promoting Db2 as a standalone platform towards including it in much broader solution portfolios such as the IBM Hybrid Data Management platform and IBM Cloud Pak for Data that combines data management with governance, DataOps, business analytics, and AI in a streamlined hybrid- and multi-cloud-ready deployment architecture.
Microsoft is a multinational technology company headquartered in Redmond, Washington, USA. Founded in 1975, it has risen to dominate the personal computer software market with MS DOS and Microsoft Windows operating systems. Since then, the company has expanded into multiple markets like desktop and server software, consumer electronics and computer hardware, mobile devices, digital services, and, of course, the cloud. Microsoft is the world’s largest software vendor and one of the top corporations by market capitalization. The company is also one of the leading cloud service providers, operating the Microsoft Azure cloud platform since 2010.
Microsoft Azure offers a broad portfolio of fully managed database engines for various usage scenarios, including a family of Microsoft’s own Azure SQL databases that help customers migrate from their on-premises Microsoft SQL Server databases to the cloud at their own pace. The company offers a choice of hosting SQL workloads on Azure Virtual Machines to maintain full compatibility, modernize existing applications for the cloud with Azure SQL Managed Instances, or become fully cloud-native with serverless Azure SQL Database.
As an alternative to a relational database, Microsoft offers Azure Cosmos DB – a fully managed multi-model NoSQL database service with multi-master replication, automated scalability, and performance guaranteed by an SLA. This database is optimized for mission-critical applications, IoT device telemetry, business analytics, AI projects, and so on. Finally, several open-source database engines like MySQL, MariaDB, PostgreSQL and Redis are available as fully managed services as well.
Traditionally for Microsoft, a rich set of developer tools (such as Visual Studio or GitHub), SDKs, and APIs, as well as DevOps technologies are available for faster application development and migration to the cloud. In addition, customers can take advantage of a multi-layered security architecture that combines network security, data encryption, access management, and threat detection.
As one of the major cloud service providers, as well as a veteran database vendor (to say nothing about a leading operating system, identity management, and development tools), Microsoft is perhaps the only software vendor that is capable of providing a full stack of products and services to power enterprise-grade cloud-native applications throughout their whole lifecycle. And not just for Windows.
MongoDB, Inc. is the company behind the popular open-source database MongoDB. Founded in 2007 in New York, NY, the company has a strong global presence with over 30 offices around the world. Designed from scratch as a general-purpose database platform for the cloud age, MongoDB has grown into the world’s fastest-growing NoSQL ecosystem and one of the preferred engines for modern cloud-native applications. The company maintains the open-source project, offers a commercial edition for enterprise customers, and operates managed, cloud-based database services across all major public clouds.
MongoDB is a general-purpose, document-based, distributed database. With elastic vertical or horizontal scalability, built-in replication, and fast automated failover, it’s been designed from scratch for cloud-scale deployments. With over 85 million users, MongoDB is arguably the world’s most popular NoSQL database. In the latest release, several major improvements have been implemented, including enhancements in the MongoDB Query Language, automated scaling, and performance tuning of MongoDB clusters. The announcement coincided with the launch of MongoDB Cloud – a unified, fully managed data platform for modern applications.
The core of the platform is MongoDB Atlas, the company’s managed database service that supports fully managed deployments of MongoDB clusters in any region of the AWS, Azure, or GCP clouds. Besides providing a single pane of glass management console across three clouds, Atlas provides integrations with various native services of each CSP, such as data streaming, serverless computing, or AI capabilities. Atlas-managed database clusters support automated scaling to meet computing and storage requirements and produce proactive recommendations for further performance optimization.
A number of additional services like Atlas Search, a built-in full-text search solution, or Atlas Data Lake for querying unstructured data stored in Amazon S3 buckets form the data foundation layer of the MongoDB Cloud platform. On top of this, application services such as serverless functions, data visualization and analytics, mobile device synchronization, and a multitude of developer tools ensure that MongoDB Cloud is a one-stop platform for developing modern highly scalable, and distributed cloud-native applications.
MongoDB and the MongoDB Cloud platform provide a simple, universal alternative for developers that do not want to replicate the complexity of their legacy on-prem infrastructures in the cloud and would rather avoid a plethora of specialized database engines, opting instead for a single interface to manage, query and analyze all of their data.
Nutanix, Inc. is a cloud computing company well-known for its hyper-converged infrastructure and software-defined storage solutions. Founded in 2009 in San Jose, California, Nutanix currently has over 80 offices around the world. The company’s portfolio encompasses a broad range of cloud-focused products, from low-level storage up to fully managed services like disaster recovery. In 2018, Nutanix launched Era, to simplify and automate database management. This solution powers the company’s DBaaS offering which is a part of the Nutanix Hybrid Cloud Infrastructure.
The Nutanix Hybrid Cloud Platform utilizes hyper-converged infrastructure to virtualize the entire data center stack along with computing, storage, and storage area networking. This software-defined infrastructure delivers major benefits of a cloud environment – such as management simplicity and flexibility – without the danger of a vendor or CSP lock-in.
Nutanix Era adds another layer to this platform, greatly simplifying and automating database operations for multiple commercial and open-source database engines. As opposed to similar offerings from major cloud service providers, Nutanix Era can be deployed either on-premises or in any public cloud that offers bare metal instances to run AOS (Nutanix Clusters). The product offers a single unified UI for provisioning, operations, and maintenance of a variety of database engines, completely hiding the complexity of underlying infrastructure and management like in a “traditional” DBaaS without handing the control over the sensitive data to a third party. Since all operations are accessible via CLI tools and APIs, the platform can be easily integrated with CI/CD pipelines, DevOps, and DataOps workflows.
Thanks to the underlying hyper-converged storage platform, operations like database snapshots and cloning are “thin” and extremely efficient. Extensible workflows and scripting enable advanced functionality like masking sensitive data during cloning. Database clones remain writable and refreshable from the original instance, essentially providing data virtualization functions for Nutanix Era users.
Technically speaking, Nutanix Era is not a Database-as-a-Service solution, since it does not let customers hand the management responsibilities over to a third party like a cloud service provider. However, for enterprises operating in strictly regulated industries or dealing with highly heterogeneous IT environments, the alternative approach offered by Nutanix might be exactly the right combination of flexibility, automation, performance while retaining full control over their business-critical data.
Oracle Corporation is an American multinational information technology company headquartered in Redwood Shores, California. Founded back in 1977, the company has a long history of developing database software and technologies; nowadays, however, Oracle’s portfolio incorporates a large number of products and services ranging from operating systems and development tools to cloud services and business application suites.
With over 40 years of expertise, Oracle is a leading solution provider for enterprise transaction processing, data warehousing, and mixed database workloads. The core technology that provides the common foundation for the entire Oracle’s database services portfolio is Oracle Database, a multi-model database management system that combines a traditional relational database with NoSQL data models like JSON, key-value, and even HDFS file formats such as Parquet.
Although Oracle is a relative latecomer to the cloud service market, Oracle Cloud is currently growing at an impressive rate, planning to surpass all other major CSPs by 2021. Co-managed and Autonomous database services are a major part of the company’s cloud strategy, making Oracle Database available in a public cloud or in a Cloud@Customer private cloud format, either on commodity hardware or on highly optimized Exadata infrastructure.
Oracle Autonomous Database, launched in 2018, completely automates provisioning, management, tuning, and upgrade processes of database instances without downtime, not just substantially increasing security and compliance of sensitive data stored in Oracle databases, but also noticeably reducing operational costs in the cloud. Since 2020, autonomous database services are available on-premises as well (or even as a part of Oracle Dedicated Region with over 50 managed services), delivering a truly unified “hybrid-native” platform for managing enterprise data at the cloud scale, while retaining the level of security and compliance previously available on-premises only.
Complemented by the “security by design” approach that incorporates data protection and privacy controls into every layer of the company’s cloud infrastructure and highly competitive cloud service pricing, this makes Oracle Cloud a compelling alternative to its more established competitors, especially for enterprises operating in highly regulated industries or having massive egress traffic requirements.
6 Vendors to Watch
In addition to the vendors evaluated in detail in this Leadership Compass, there are several companies that for various reasons were unable to participate in the rating but are nevertheless worth mentioning in this chapter.
6.1 Google Cloud
Google LLC is a multinational company specializing in internet-related products and services, known primarily for its search engine, online advertising technologies, and cloud computing services. Launched in 2008, Google Cloud is the company’s suite of cloud computing infrastructure services, which also powers Google’s own SaaS offerings like G-Suite and YouTube. Together with AWS and Microsoft, Google Cloud is recognized as one of the leading public cloud service providers.
With regards to database-related cloud projects, Google Cloud has a broad portfolio of services that can address almost any customer use case: from lifting and shifting open-source databases to GCP with services like Cloud SQL for MySQL or PostgreSQL to rehosting enterprise databases like Oracle with Bare Metal Solution to adopting properly cloud-native database solutions like Cloud Spanner (a massively scalable fully managed relational database), Bigtable (fully managed service for analytical or operational workloads) or Cloud Firestore (a NoSQL database for mobile and web development). Of course, Google’s database services benefit from deep integrations with other GCP services, such as BigQuery serverless analytics or GKE container orchestration.
6.2 SAP HANA Cloud
SAP is a multinational enterprise software vendor headquartered in Walldorf, Germany. The company is primarily known for its enterprise resource planning (ERP) software and other solutions for managing business operations. Since 2010, the company offers a column-oriented, in-memory database platform SAP HANA, which is designed to support both transactional and analytics workloads for business-critical high-performance operations.
Since 2015, SAP’s flagship business application suite is powered exclusively by the HANA platform. However, the company also offers SAP HANA as a general-purpose platform for developing enterprise data solutions, combining data management, advanced analytics, application server, and development tools in a single managed DBaaS offering. Many major cloud service providers support HANA deployments on their infrastructures, but SAP itself currently offers it as well, both as a private SAP HANA Enterprise Cloud and as a part of SAP Cloud Platform, the company’s integration and extension platform-as-a-service.
Besides these major vendors, we would also like to mention several smaller companies, which offer innovative, if somewhat more narrow-focused solutions for various cloud database-related use cases. Some of these aren’t even database vendors in a strict sense, but their products might simplify, optimize, or otherwise improve cloud migration projects of a particular kind.
EnterpriseDB is a privately held company based in Bedford, MA. Since 2004, the company has been providing enterprise-grade database solutions based on the popular Open Source PostgreSQL database engine. With numerous enhancements in availability, performance, and security and additional management tools in the EDB Postgres Platform, EnterpriseDB offers an enterprise-grade database solution that can be deployed in a wide variety of environments.
Since 2018, the company offers EDB Postgres in the Cloud as a range of cloud-based database deployment options including a fully-managed database as a service offering. Customers can deploy a Postgres cluster in minutes and run it in a native Oracle compatibility mode to simplify the migration of existing applications.
6.4 MariaDB SkyQL
MariaDB is a commercially supported open-source database, developed and maintained by the original developers of MySQL, arguably the most popular relational database in the world. After MySQL was acquired by Oracle in 2010, MariaDB was forked to ensure its continued availability as an open-source project and drop-in replacement compatibility with MySQL.
Currently, MariaDB Enterprise Server is an enterprise-grade open source database that supports different workload types with pluggable engines, offering a single solution for transactional processing, interactive analytics, and even document model support, optimized for massive scalability, advanced security, and integrations with Apache Kafka and Redis for enterprise deployments. Although managed MySQL and MariaDB are available from any reputable cloud service provider, in 2020 the company has introduced SkySQL, its database-as-a-service offering guaranteed to run the latest stable release of the software and avoid any potential proprietary API lock-ins.
NuoDB is a database vendor based in Cambridge, Massachusetts. The company was founded in 2008 by a group of industry experts with a vision to reinvent relational databases for elastic scalability. NuoDB’s database technology is based on a distributed object architecture comprising multiple tiers of storage management and transaction engine nodes. This approach enables elastic scaling without sharding, essentially combining scalability of NoSQL databases with enterprise capabilities of relational solutions.
Since 2015, NuoDB is available as a distributed SQL database for mission-critical applications, which can be deployed on-premises or in multiple public or private clouds. The solution is not intended to be a drop-in replacement for traditional relational databases, since it requires rearchitecting both infrastructure and code to achieve optimal performance, so the company primarily focuses on large enterprise companies in the financial sector.
6.6 Redis Enterprise Cloud
Redis Labs, based in Mountain View, California, is the company providing development and commercial support for Redis, one of the world’s most popular NoSQL databases. Launched in 2009, originally as an open-source caching solution for improving application performance, over the years Redis has evolved into a distributed in-memory data structure store, which combines the functions of a database, a cache, and a message broker.
With the support of a broad range of data structures, optional on-disk persistence, high availability and clustering, and a large number of SDKs for various languages, Redis has become one of the most popular solutions with developers of business-critical applications. Its architectural simplicity allows for deployment flexibility: from bare metal and virtual machines to containers and Kubernetes to every notable cloud platform.
Redis Enterprise Cloud is the company’s fully managed Database-as-a-Service offering that gives customers a choice of several major public cloud infrastructures, as well as all the advanced performance and security features of the latest Redis Enterprise release.
6.7 Snowflake Cloud Data Platform
Snowflake Inc. is a cloud data management company headquartered in San Mateo, California. Founded in 2012 by a group of data warehouse experts, the company is focused on offering a cloud-native, managed alternative to conventional Big Data platforms to spare customers from their complexity and scale limitations.
Snowflake’s Cloud Data Platform is a fully managed data warehousing and analytics platform-as-a-service running on major public clouds: AWS, Azure, and Google Cloud Platform. Its distributed, cloud-agnostic architecture allows enterprise customers to break away from the traditional siloed approach and consolidate all their data warehouses, data lakes, data pipelines on a single cloud-native foundation. With all infrastructure management taken away from users, they can focus on business-relevant aspects of data management and analytics or enable easy yet secure sharing with their customers and partners.
6.8 Teradata Vantage
Teradata Corporation is a data management and intelligence vendor headquartered in San Diego, California. Founded in 1979, the company is one of the veteran players in the big data management and business analytics market. Although Teradata’s original technology and solutions predate the cloud, nowadays the company offers a broad range of cloud-native and hybrid solutions.
Teradata Vantage is the company’s “pervasive data intelligence” platform, a solution that unifies all data warehouses or data lakes across an organization in one place (both on-prem and in the cloud) to enable business intelligence across it with a broad range of languages and tools. It allows storing and analyzing data in various formats with rich visualization and machine learning capabilities.
Tidalscale is a provider of software-defined server solutions for data centers and the cloud. Founded in 2012 in Campbell, California, the company offers a unique approach towards solving scalability issues of big-scale data workloads. Instead of deploying complex and costly infrastructures or re-platforming existing applications to support cloud-native databases, TidalScale aggregates computing and memory resources of multiple physical servers or compute instances in the cloud into a single virtual server.
Any existing application, including database management or analytics software, can run on these servers without any modification, achieving fully elastic in-memory performance for workloads of any size. The platform can even utilize machine learning to automatically optimize its resource utilization based on your application behavior. The company offers turn-key solutions for popular workloads like Oracle, SAP HANA, and big data analytics.
7 Related Research
KuppingerCole Analyst Chat: Enterprise Databases in the Cloud
Leadership Compass: Database and Big Data Security – 79015
Leadership Compass: Infrastructure as a Service – Global Providers – 80035
Leadership Compass: Privileged Access Management – 80088
Advisory Note: Your Business is Moving to the Cloud – 71156
Advisory Note: Selecting your cloud provider – 70742
Advisory Note: Cloud Services and Security – 72561
Advisory Note: Database Governance – 70102
Leadership Brief: Introduction to the Information Protection Life Cycle and Framework – 80370
Leadership Brief: Data Security and Governance (DSG) for Big Data and BI Environments – 80109
Executive View: AWS Security Analytics Solutions – 80220
Executive View: Delphix Dynamic Data Platform – 79010
Executive View: Google's Cloud Identity – 80326
Executive View: IBM QRadar Security Intelligence Platform – 72515
Executive View: Oracle Autonomous Database – 70964
Executive View: SAP HANA Platform Security – 70272
Snapshot: IBM InfoSphere Guardium – 70632