According to TheRegister.com, Snowflake has open-sourced its PostgreSQL extensions called pg_lake in a bid to attract developers and data engineers to integrate the popular open source database with its lakehouse system. The extensions were developed by PostgreSQL specialist startup Crunchy Data before Snowflake acquired the company for $250 million in June this year. Available under the Apache license, pg_lake allows developers to read and write directly to Apache Iceberg tables from PostgreSQL, eliminating the need to extract and move data. Snowflake executive vice president Christian Kleinerman said this would let PostgreSQL users turn the database into an interface for managing an open lakehouse. The company also announced general availability of Snowflake Intelligence, an AI agent for natural language queries, alongside additions to its Horizon data catalog.
<h2 id="postgresql-play“>The PostgreSQL play
Here’s the thing about this move – it’s actually pretty smart. Most organizations aren’t going to rip out PostgreSQL, as analyst Robert Kramer pointed out. It’s everywhere. So instead of fighting that reality, Snowflake is embracing it. They’re basically saying, “Hey, keep your PostgreSQL – just let us connect to it.” The pg_lake extensions let PostgreSQL act as the catalog for Iceberg tables, which is a clever way to make Snowflake’s platform feel more integrated rather than like a separate system.
The Databricks rivalry heats up
Now, let’s talk about the elephant in the room – Databricks. They’re the ones who introduced the lakehouse concept five years ago, and Snowflake has been playing catch-up in some ways. But this move shows Snowflake’s strategy is different. They’re not trying to replace everything – they’re trying to become the analytics layer that works with whatever you already have. The company’s blog posts emphasize making data available for analytics without forcing architectural changes. That’s a much softer sell than “rip and replace.”
Where AI fits in
So where does AI come into this? Well, Snowflake Intelligence is their new AI agent that answers complex questions in natural language. But Kramer makes an interesting point – buyers might need help understanding how Snowflake is different from Databricks and other platforms when it comes to AI. Snowflake’s pitch seems to be about reliable, responsible AI for real operations, not just experimentation. The engineering blog details how this connects to their broader platform strategy. But they still need to prove they can handle scale, monitoring, and real-world costs for agent workloads.
What this actually means for developers
Basically, if you’re a PostgreSQL shop, Snowflake just made it way easier to dip your toes into their ecosystem. You don’t have to commit to a full platform migration. You can start using Snowflake for high-value analytics while keeping your operational databases right where they are. That incremental adoption approach is probably going to work better than expecting companies to make huge platform decisions all at once. And let’s be honest – in today’s economic climate, nobody wants to explain to their CFO why they need to replace a perfectly good PostgreSQL implementation.
