Equity Research Technology, Media, & Communications | Enterprise and Cloud Infrastructure March 22, 2019 Industry Report Jason Ader +1 617 235 7519 [email protected] Database Software Market: Billy Fitzsimmons +1 312 364 5112 The Long-Awaited Shake-up [email protected] Naji +1 212 245 6508 [email protected] Please refer to important disclosures on pages 70 and 71. Analyst certification is on page 70. William Blair or an affiliate does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. This report is not intended to provide personal investment advice. The opinions and recommendations here- in do not take into account individual client circumstances, objectives, or needs and are not intended as recommen- dations of particular securities, financial instruments, or strategies to particular clients. 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William Blair Contents Key Findings ......................................................................................................................3 Introduction .......................................................................................................................5 Database Market History ...................................................................................................7 Market Definitions .............................................................................................................9 The DBaaS Wave ..............................................................................................................18 Sizing the Operational Database Market ........................................................................19 The Open Source Insurgency ..........................................................................................29 The Pull of the Cloud .......................................................................................................35 Rise of Containers and Microservices .............................................................................35 Competitive Landscape ...................................................................................................37 Private Company Profiles ................................................................................................46 Appendix: Glossary of Terms ..........................................................................................62 2 Jason Ader +1 617 235 7519 William Blair Key Findings Exploding volume of data + changing nature of applications + cloud adoption + open source = database market disruption. Ninety percent of the world’s data was created in the past two years alone, according to Forbes. At the same time, lines of business are increasingly demanding a broader set of applications that can harness data to drive digital transformation. Many of these applications are cloud-native, and a growing percentage are being built on a microservices architecture. All of these applications must be supported by an underlying database, which increasingly is based on innovation in the roughly $30 billion operational database management system (ODBMS) market. open-source software. The confluence of these trends is driving disruption, fragmentation, and Proliferation of database types has driven market confusion. To keep pace with the surging volume of data and changing nature of applications, the database itself has undergone a transfor- mation. This has fueled the emergence of a plethora of database types and vendors over the past (on-premises, cloud, hybrid) and different ways data can be stored (multiple database models) have ledseveral to hype years and geared market toward confusion, specific though use-cases. the dust However, appears theto be different settling places as customers data can learn be storedwhich products/vendors work best for different use-cases. It’s all about the use-case. Our research indicates that the historical distinction between relational databases (where data is organized by rows and columns) and nonrelational databases (where databases (e.g., MongoDB) can increasingly address transactional use-cases like order processing, whichdata is rely organized on data in of meansrecord other(the historical than rows purview and columns) of relational is blurring. DBs). Conversely, Specifically, some nonrelational relational DBs (e.g., Google Cloud Spanner) can address use-cases like gaming, which require distributed scal- ing (the historical purview of nonrelational DBs). Over time, this suggests that the religious debate on relational versus nonrelational will give way to a more pragmatic database selection process centered on use-case suitability. Secular shift toward nonrelational DBs, but death of relational DBs is greatly exaggerated. We expect continued rapid adoption of nonrelational DBs alongside the boom in unstructured and scalability inherent in a nonrelational DB. Put simply, nonrelational DBs are better aligned withdata moderncreation applications, and next-generation, agile software cloud-native development, applications and the thatburgeoning demand DevOps the speed, ecosystem. flexibility, Yet we do not believe this will eliminate the need for relational databases, which will continue to be heavily utilized for mission-critical, transactional applications (as well as for complex query data warehousing) and for which there remains substantial organizational inertia. To put this in con- text, IDC forecasts that relational DBs will still account for more than 80% of the total operational database market by 2022, though we suspect that this prediction is too conservative with respect to nonrelational DB adoption. DBaaS (database-as-a-service) is becoming table stakes. The DBaaS model has taken the market by storm in recent years as it frees up developers from self-hosting and managing what is arguably worrying about managing and tuning the database (and its underlying infrastructure)—which is outsourcedthe most complex to the DBaaSand difficult-to-manage provider—developers layer areof the able application to focus on stack building (the applicationsdatabase). Instead with the of speed and agility necessary in today’s information-driven economy. Sold as a fully managed, sub- scription service by a CSP (cloud service provider) or independent database vendor (running on a public or private cloud), a DBaaS virtualizes the database from the application, allowing the database to be run and managed independent of the application (this is especially useful for microservices- based applications). For DBaaS vendors, a primary appeal is the ability to monetize free usage of open-source database software. Jason Ader +1 617 235 7519 3 William Blair Multimodel databases are taking hold. To address market fragmentation and the resulting customer confusion, vendors have introduced multimodel databases, which incorporate multiple database structures in the same package, enabling data to be represented for numerous use-cases - plication being addressed). As noted above, these general-purpose databases can even offer both simultaneously (with the choice of mode based on what is most appropriate for the specific ap throat-to-choke approach will appeal to certain users, we still see room for specialized databases suchrelational as graph and and nonrelational time-series capabilitiesto be successful in the given same their platform. uniqueness While and this unmatched one-size-fits-all, performance one- Open-sourcefor specific use-cases. databases becoming more closed. The developer-centric nature of the operational database market explains in large part the popularity and proliferation of open-source offerings (about 170 open-source databases out there today, according to website DB-Engines), and com- mercial open-source vendors rely on the “freemium” model to spur adoption of their paid solutions. projects like MongoDB, Redis, and PostgreSQL has spurred a backlash among open-source vendors. TheseHowever, vendors the ability believe of thatcloud CSPs providers are unfairly to develop monetizing commercial open-source DBaaS softwareofferings while from contributingopen-source little to the community. As a result, several open-source vendors, including MongoDB and Redis Labs, sell services based on their open-source technologies – although there is still no consensus in the openhave attemptedsource community to institute for morehow to restrictive deal with licensing so-called models CSP “strip to make mining.” it more difficult for CSPs to Streaming data will increasingly be used for operational purposes. (e.g., machine-generated data) was used only for analytical purposes, but with advances in memory and chip processing it is now possible to process streaming data in real-time.Historically, With streamingthe emergence data of internet of things (IoT), more data will be created in real-time, and enterprises will want and need to harness this real-time data to deliver personalized experiences to customers and extract - optimizeinstantaneous the routes insights taken for bystrategic its delivery decision-making vehicles. and business efficiency. For example, a pack age delivery company could blend real-time traffic data together with customer pickup requests to Growing convergence of transactional and analytical databases. - Historically, the