I Built a Database That Never Forgets — Here's Why

Last year, a financial services team I was working with had a nightmare scenario: a regulatory audit required them to prove exactly what their system showed on a specific Tuesday six months ago. Not what the data currently says. What it said then . Their production Postgres had the current state. Their audit table had some breadcrumbs. Their application logs were partially rotated. Reconstructing the answer took two engineers three weeks of forensic archaeology through backups, WAL archives, and prayer. This is the problem that drove me to build TensorDB . The Problem With UPDATE Here's what most databases do when you update a row: UPDATE accounts SET balance = 5000 WHERE id = 1 ; The old value is gone. Destroyed. Overwritten. If you need history, you build it yourself — trigger-based audit tables, event sourcing patterns, CDC pipelines feeding into a data lake. You end up with a Rube Goldberg machine of infrastructure just to answer "what was this value last week?" Bitemporal database