Postgres: The Friendly Relational Member of Your Data Management Toolbox
While every year feels like the year of Postgres these days, 2012 did not. For most observers, 2012 was the year of "Big Data" as NoSQL technologies like Hadoop and MongoDB were demonstrating powerful new data management use cases.
At the same time, Crunchy Data was still just an idea and was beginning to engage with various consumers of database technology on how this wave of new open source tools were impacting their data strategy. During these early discussions - and many since - we heard how organizations were building a modern data management toolbox. The tools were being selected to support the next generation of application development. Organizations were including a NoSQL tool like Hadoop, one or two legacy databases, a data caching or message broker technology, and a modern relational tool as the new SQL standard. And the relational database tool of choice that we heard about time and time again, was Postgres.
Despite the enthusiasm for Big Data, the macro trend driving change in how organizations think about databases, the more nuanced trend was toward open source software as both a viable and innovative solution to data problems. While Linux was an increasingly well-established operating system of choice, prior to the Big Data movement, open source data tooling was still relegated to the early adopters and enterprise "exception" servers. For Big Data in 2012, open source was not only a credible option, it was the only option for addressing these new challenges.
No more. As organizations began to get comfortable with open source for their "NoSQL" data stores, the next logical question was,"Why not use open source for our relational databases?" The death of relational and SQL was grossly overstated, and the forward thinking users were betting on Postgres as their relational database for the future.
As organizations re-evaluated their long held data management perspective, Postgres was ready and waiting. What began as a well thought out codebase at UC Berkeley had developed into a rock solid and full featured relational database ready to take on all sorts of workloads.
Postgres was steadily innovating as a community-driven open source database, adding new capabilities with each release. Users who had looked at Postgres long ago were surprised to learn that it now supported native replication, JSONB, query parallelism, and partitioning. This was on top of many features that had Postgres at parity with other relational databases, such as multi-version concurrency control, native procedural language support (PL/SQL, Python, Perl, R), advanced authentication mechanisms (certificates, Kerberos, ActiveDirectory) and more. With each release, the Postgres community brought it closer to readiness for the wide range of applications backed by relational databases, along with the wide range of Postgres extensions like PostGIS that enable even more rapid innovation and workload specific capabilities.
We at Crunchy Data have continued to be impressed by the Postgres community and its steady innovation. Year after year, the project gets better. The rise of the cloud and new platforms such as Kubernetes have only accelerated the trend toward open source infrastructure, and open source data management by extension.
The recent selection of Postgres as the "Database of the Year" for the third time in four years is by no means an overnight success story, but is well deserved recognition for a database decades in the making. As organizations look for the relational database of the future, Postgres is ready and waiting. We are proud to be among the leading contributors and supporters of this important movement.
January 15, 2021 •More by this author