For years open source and non-relational data have upended the decades’ old dotage of database technology. In 2018, for example, Gartner projected that open source databases would account for “10% of DBMS spending, reflecting accelerating adoption by enterprise users.” This rising open source tide hasn’t raised all boats, with Oracle continuously losing market share since 2013, according to Gartner.
As important as open source has been, and as disruptive as non-relational databases like MongoDB remain, there’s a far bigger trend in database adoption, and it’s all about cloud. As a recent 451 Research survey indicates, cloud is the biggest shift in database adoption by far.
SEE: How to build a successful career as a cloud engineer (free PDF) (TechRepublic)
Born in the cloud
When 451 Research polled a representative sample of IT executives, it uncovered some unsurprising trends. Across the board, enterprises are looking to new ways to manage their data. Relational databases, so convenient for a cozy world of data stored in neat-and-tidy rows and columns for ERP and other systems, have increasingly lost their luster in a world of high volume, high velocity, and highly variable data. Suddenly more flexible schema, offered by non-relational databases like MongoDB or Apache Cassandra, are critical.
In addition, given the central role of developers in the modern enterprise, open source keeps gaining in importance, as it gives developers immediate access to the code they need. This has led to the introduction of new vendors to satisfy new database workload needs.
All of which shows up in the 451 Research data, as enterprises “swing to” the future of data (Figure A).
Notice that as important as open source and non-relational databases are, the far bigger trends driving database adoption are the kissing cousins of scale-out architectures and cloud computing.
Two ways to think of cloud
There are at least two explanations for this. The first, relative to a shift from scale-up to scale-out architectures, has everything to do with volume. Quite simply, enterprises are dealing with far more data today than they were a decade ago, or even a year ago. While non-relational databases contribute to resolving the scale problem, cloud is a far bigger contributor to its resolution. At the same time, that volume of data tends to be born in the cloud today. Data gravity being what it is, it makes sense to manage this data in the same place where it was created.
But there’s another reason that cloud adoption is off the charts: Cloud computing fulfills many of the promises of open source, while also enabling the promise of non-relational databases. In the cloud, you don’t really have to choose. If you want MySQL or PostgreSQL running at scale, you can get those from one of several cloud providers. Or if you want Amazon’s DocumentDB, MongoDB, Redis, Cassandra, Google Cloud Datastore, or another non-relational database, you can get that, too.
For developers, they get the choice they’re used to from open source, but with added convenience. Rather than having to provision servers, the clouds take care of it for them. Years ago, Tim O’Reilly’s words on “open enough” data still ring true for cloud databases:
There’s a pragmatic open and there’s an ideological open. And the pragmatic open is that it’s available. It’s available in a timely way, in a non-preferential way, so that some people don’t get better access than others….When the cost is low enough, it does in fact create many of the same conditions as a commons.
Or, as Tom Barber has noted of the relative importance of “open” vs. “cloud” for developers, “There’s a shift from ‘We need the source code to make changes and get a consultant to implement it’ to ‘we can get this stood up really quick and supported by our favorite cloud vendor.'” Convenience, it turns out, trumps all.