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We are excited to announce that Crunchy Data is joining Snowflake to bring Postgres to the AI Data Cloud.
Long Live SQL
While every year feels like the year of Postgres these days, 2012 did not. For most, 2012 was the year of "Big Data" as NoSQL technologies were demonstrating powerful new data management use cases, and the idea of building a new company around SQL technology was either foolish or contrarian depending on who you asked.
At the same time, Crunchy Data was still just an idea and was beginning to engage with various consumers of database technology. 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.
The relational database tool of choice that we heard about time and time again, was Postgres. 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 reevaluated long held data management perspectives, Postgres was ready and waiting. Over the years, Postgres has continued its steady innovation as a community-driven open source database by 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. With each release, the Postgres community brought it closer to readiness for the wide range of applications, along with the wide range of Postgres extensions (like PostGIS) that enable rapid innovation and workload specific capabilities. As the requirement for AI enabling data workloads emerged, the Postgres community rapidly innovated around pgvector supporting performant vector management natively in Postgres.
Since 2012, Crunchy Data has been proud to play its part within the Postgres community by giving longtime contributors the ability to continue to build Postgres as a truly community-driven open source database project and allowing organizations to confidently deploy the leading open source database technology.
Bringing Postgres to Cloud Native
Meanwhile the trend towards data management in the cloud has been undeniable. Over the years we’ve become more invested in the cloud. What began with the simple idea of running Postgres in a container became one of the first stateful Kubernetes Operators to exist. The team at Crunchy Data blazed a trail for Kubernetes to be viable for stateful workloads. Today Crunchy’s Postgres Operator for Kubernetes is used in production by organizations of all sizes.
While many organizations wanted the control and flexibility enabled by Kubernetes, many wanted the experience of a fully managed Postgres service. When managed Postgres in the cloud first emerged, there was an open question as to whether organizations would have the confidence to run their data in the cloud. Leaders like Amazon and Snowflake demonstrated that could be done in a secure way, building the trusted infrastructure for organizations to confidently manage data in the cloud. What began as an emerging trend of managed Postgres rapidly became the leading deployment model and it was clear that Crunchy Data needed a fully managed Postgres offering to complement the strength of its enterprise Postgres
In 2019, we made a very intentional bet to build the first 'pure play' Postgres managed service. What if there was a better cloud experience that existed? The team that we recruited had been growing the Postgres world since the same time as Crunchy Data’s origin, though from a different side. Today, Crunchy Bridge is a best-in-class Postgres managed service designed to be production-ready out of the box. It provides a developer-friendly Postgres experience with the ability to scale and support both large applications such as YNAB and Moneytree and developer side projects with hobby plans starting at $10 a month.
Convergence of Data Workloads
While more and more workloads moved to Postgres, users pushed the database to address a broader range of workloads.
The one area in which PostgreSQL has historically been lacking is analytics, which involves queries that summarize, filter, or transform large amounts of data. Over the past few years we have increasingly seen our customers interested in pairing Postgres operational database capabilities with analytics engines. Users want their operational data to also be seamlessly available for analytics. They want the ability to benefit from cloud-native, low-cost storage. Those trends drove us to develop innovative capabilities at the intersection of Postgres and Apache Iceberg.
In our discussions, it quickly became clear that the same trends that Crunchy Data was seeing from the operational database world were also apparent to Snowflake. Snowflake believes that Postgres is the leading operational database and wants to bring Postgres into the Snowflake AI Data Cloud. With today's announcement, we are targeting the large online transactional processing (OLTP) market, leveraging Snowflake's reach and Crunchy Data's flexible, scalable solutions for enterprise workloads and developers alike.
Next Chapter
With this announcement, we look forward to the next chapter of enabling Postgres adoption at an even larger scale. Joining Snowflake creates the potential to expand our contribution to the Postgres ecosystem and community. Our team at Crunchy Data will be joining the team at Snowflake in driving new innovation in Postgres in the trusted Snowflake Data Cloud, while continuing to provide the production-ready Postgres technology with the leading developer experience that our customers rely on.
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