Usage grew through the back half of 2025 and the product started to show it. Enrichment queues ran longer than they should have, and tables past a thousand rows felt heavy. So we stopped shipping features for two months and spent the time on infrastructure instead.

Queues that hold up under load

The enrichment queue layer was rescaled and hardened. Jobs run faster and, more importantly, keep running when the platform is busy rather than backing up behind each other.

Tables that stop lagging

Tables use significantly less memory than they did, and the difference shows as they grow. Scrolling, editing and updating now feel closer to a spreadsheet than a web app waiting on a server.

Infinite scroll

Tables used to load 600 rows at a time, so reaching the end of a large dataset meant waiting through several batches. Scrolling is now continuous: jump to the middle or the very end immediately, whatever the size.

A faster JSON Expander

Exporting several values out of a JSON cell into new columns runs up to six times faster. The values are processed in parallel and land together, which removes the UI stall and takes pressure off the enrichment queue at the same time.

Faster to load, everywhere

Large parts of the front end were reworked, so initial load and general responsiveness improved across the app.

None of this is a feature you can point at in a screenshot. It is the work that decides whether the features you already use are pleasant at scale.

About Databar

Databar replaces your go-to-market data stack with one platform. Search companies, people, and jobs, monitor the web for signals, and enrich it all with 160+ data sources and waterfalls. Wire everything into reusable automations that run on a schedule, on your tables and CRM data, or by an AI agent. App, API, MCP server, SDK, and CLI included on every plan.