Databricks cost management, job by job.
Databricks cost work breaks down into a handful of recurring jobs: attribute the spend, watch it for anomalies, bill it back, find the waste, and keep an eye on all of it. Each page below covers one of them — what native tooling gives you, where it stops, and how LakeSentry handles it.
Cost attribution
Map every cost line to a team with rules, mappings, and session-based splits, each allocation labeled with its confidence tier.
Learn moreAnomaly detection
Seven statistical detectors watch every workspace; each alert arrives with its baseline, z-score, and dollar delta.
Learn moreChargeback
Org → department → team rollups on defensible attribution, with split rules for shared costs and CLI export to billing systems.
Learn moreWaste detection
Idle compute, retry storms, unused tables, oversized resources, detected across workspaces and ranked by observed cost.
Learn moreCost monitoring
One normalized ledger across every workspace, explorable by team, job, and warehouse — with a baseline kept for every workload.
Learn moreComparing tools?
Native tooling, LakeSentry, Unravel, PointFive, Espresso AI, and the rest of the landscape — by scope, pricing, and automation model.
See the comparisonOr Start From Your Role
The same platform, framed for the chair you sit in.