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.

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.

What are Databricks system tables?

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