Databricks is acquiring Electric, the startup behind the WASM Postgres project PGlite, in a move that signals a shift towards providing AI agents with their own databases.
The acquisition is a bet that AI agents need thousands of tiny, disposable databases and a sync engine to hold them together.
The Electric team will join Neon, the serverless Postgres company Databricks acquired for about $1 billion last year, and the foundation of its Lakebase database service.
They didn’t disclose the terms of the deal.
PGlite is a complete Postgres database in WebAssembly that runs in the browser, a Node.js process, or inside the kind of sandboxes agents use to execute code.
It supports dynamic extension loading, including pgvector, the preferred Postgres vector extension.
According to the companies, PGlite has grown from 1 million to 13 million weekly downloads over the last year.
The Electric sync engine is core to Databrick’s interest in Electric, as it keeps a central Postgres database that can then be synced in near real-time with browser tabs, mobile apps, or agents.
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This engine is similar to the multiplayer model of Figma or Google Docs, but applied to Postgres and the agents that use it.
Building a real-time sync engine from scratch is difficult due to complex problems like conflict resolution, partial replication, and reconnection logic.
This is likely why Databricks acquired Electric instead of trying to build this from scratch itself.
As for the future of Electric, the company’s founders James Arthur and Valter Balegas write that “everything we’ve previously open sourced stays open source.”
This covers the sync engine, PGlite, Durable Streams, and TanStack DB.
What doesn’t survive the deal, however, is Electric’s hosted service. “Electric Cloud is winding down,” the founders. “Cloud users will need to self-host or move to another provider.”
The deal extends a string of database acquisitions for Databricks that includes Neon itself and, more recently, the transactional processing startup Mooncake.
In practice, a coding agent spins up a sandbox, instantiates PGlite inside it, builds and tests against the database, and then either throws the whole thing away or syncs the result with a Lakebase branch.
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Because Lakebase separates storage from compute and keeps its data in Postgres page formats on object storage, creating that branch is a relatively cheap copy-on-write metadata operation.
For some types of applications on Lakebase, the average database compute is now alive for under 10 seconds.
Agents, as it turns out, like to branch databases the way they branch code, a pattern Neon built its architecture around.
Traditional non-agentic applications share one database among many clients, and that database is the most permanent piece of the stack.
But agent workloads change this, creating a need for thousands of tiny, disposable databases.
PGlite didn’t start at Electric, instead, it began as an experiment by Neon.
Databricks continues to expand its capabilities in supporting AI agents.
