# What are Databricks system tables?

> System tables are Databricks-managed tables in Unity Catalog that record platform metadata: billing usage, cluster and warehouse configurations, job runs, query history. The cost-relevant ones, like system.billing.usage, retain a rolling 365-day window and are the raw source behind any Databricks cost analysis — native or third-party.

- Canonical: https://lakesentry.io/glossary/system-tables/
- Published: 2026-07-15

---

For cost work, four tables do most of the lifting: `system.billing.usage` (one row per billable DBU window), `system.billing.list_prices` (per-DBU rates by SKU), and the compute tables (`system.compute.clusters`, `system.compute.warehouses`, `system.lakeflow.jobs`) that attach names and configurations to the IDs in the usage rows.

The data is detailed and reliable. It is also raw. Usage rows carry IDs, not team names; dollars require joining list prices; attribution requires tags or your own mapping layer on top. System tables answer "what ran and what did it consume"; everything above that is analysis someone has to build and maintain.

They're also the boundary of what a cost tool should need. LakeSentry reads Databricks system tables — cost and usage metadata. It never accesses your business data, notebooks, or query results.