Snowflake is acquiring Crunchy Data, a leading provider of enterprise PostgreSQL solutions. This move aims to integrate Crunchy’s robust PostgreSQL capabilities into Snowflake’s AI Data Cloud, facilitating the development and deployment of AI agents and applications.
Key Points:
- The acquisition integrates enterprise-grade PostgreSQL into Snowflake’s AI Data Cloud.
- This move positions Snowflake to better compete with Databricks and others in the AI infrastructure market.
- The deal highlights the critical role databases play in the emerging "agentic AI" market
The cloud data giant announced the acquisition at its Snowflake Summit conference today, bringing about 100 employees from the Charleston-based PostgreSQL specialist into the fold. But the real story here isn't just the numbers—it's what they reveal about the frantic race to control the infrastructure that powers AI agents.
We're witnessing something of a PostgreSQL gold rush. Just three weeks ago, Databricks shelled out a reported $1 billion for Neon, another Postgres startup. Salesforce recently acquired data management veteran Informatica. ServiceNow grabbed Data.World. The pattern is clear: every major platform wants to own the data layer that feeds AI agents.
"We're tackling a massive $350 billion market opportunity," Vivek Raghunathan, Snowflake's SVP of engineering, said in the announcement. That might sound like typical corporate hyperbole, but the underlying trend is real. According to Neon's own data, over 80% of databases created on their platform were spun up by AI agents, not humans. That's a fundamental shift in how databases get used.
The appeal of PostgreSQL in this new world makes perfect sense. It's the most popular database among developers, with nearly half reporting they use it. More importantly, it's built for the kind of rapid, automated provisioning that AI agents demand. When an AI agent needs to store data or run a query, it can't wait for a database administrator to file a ticket and provision resources days later.
Crunchy Data brings something Snowflake has been missing: enterprise-grade operational database capabilities. While Snowflake excels at analytical workloads—the kind where you're crunching massive datasets—it's been weaker on the transactional side where applications store and retrieve data in real-time. The company tried to address this with Unistore, but that solution has limitations compared to a full PostgreSQL implementation.
Crunchy Data specializes in the enterprise and regulated markets that Snowflake knows well, including federal agencies and financial institutions that demand serious security and compliance features.
This all points to a broader shift in enterprise computing. We're moving from the era where humans provision and manage databases to one where AI agents do it automatically. Gartner predicts that by 2028, AI agents will be making 15% of day-to-day work decisions. When agents can autonomously create databases, analyze data, and take actions based on what they find, the database becomes less of a static resource and more of a dynamic tool.
The question for Snowflake is whether they can make up ground. Databricks' $1 billion bet on Neon signals they're serious about owning the operational database market. Meanwhile, the hyperscalers—Amazon, Microsoft, and Google—all have their own PostgreSQL offerings that work seamlessly with their broader cloud platforms.
For developers, though, this database arms race means more options and potentially better integration between analytical and operational workloads. Snowflake Postgres will go into private preview soon, and if it delivers on the promise of enterprise-grade PostgreSQL with Snowflake's security and governance features, it could simplify the often complex world of data infrastructure.