Running a team of agents to build stuff and carry out tasks for you while you touch grass just got a lot better.
On Tuesday, Databricks announced that it acquired Electric, a company that runs a lightweight database that has exploded in popularity because of its usefulness in the era of AI agents.
Technologically, Electric runs PGlite, which is a lightweight version of the popular open-source Postgres database that can run directly on a laptop, tablet, phone, browser, or AI agent sandbox using WebAssembly (WASM). This lets software developers and vibe coders do much faster and more powerful stuff straight from their mobile devices.
"You can run it in very low‑powered environments," Databricks VP of engineering Nikita Shamgunov told The Deep View. "You can run it on Raspberry Pi. You can run it on your phone. You can run it on your laptop."
PGlite enables two important things:
- By running locally, it can reduce latency, work when you have unreliable connectivity, lower cloud costs, and make agent loops faster by not needing to make a network request every time data is needed; as a result, agents can constantly read information, update their context, call tools, coordinate with other agents, and decide what to do next
- Simultaneously, Databricks and Electric pair PGlite with a real-time synchronization system that keeps those small local databases connected to Databricks' central Lakebase Postgres database; that enables developers and companies to potentially scale up the best apps and deploy them more broadly across the organization
"Before, we were bottlenecked on people typing code, and therefore the rest of the infrastructure had to go at human speed," said Shamgunov. "But now they go at machine speed… If you don't embrace that as company, your competitors will and you'll be left in the dust."
Our Deeper View #
The paradigm shift here is companies being able to safely enable software developers and team members who want to vibe code to work on much more sophisticated projects straight from their phones or tablets. At the same time, their data can be synced to an enterprise database so that the work can be centralized and have the option for wider deployment as well as dissemination of learning across the organization.