DatabricksDBU burn, flagged before finance sees it.
Workspace and SKU detail without touching system tables, plus the forecast and spike alerts the account console leaves to you.
- Read-only access
- 14-day free trial
- No credit card required
- 5 min
- setup, per provider
- 90 days
- available history
- Same-day
- anomaly alerts
Daily spend by provider
$24,321 total
See what is driving Databricks spend.
Read-only access, with nothing to install.
Billing integrations read cost and usage data without changing your provider resources. Permissions vary by provider; follow its setup guide. Claude usage uses opt-in OpenTelemetry, and custom sources use cost imports or scoped ingestion rather than a billing API.
How it worksDatabricks · illustrative connection
- Cost and usage read requests
- Permissions reviewed before connecting
- Coverage follows the provider setup guide
Every dollar has an owner.
Auto-tagging rules label costs as they are ingested, matching provider, account, service and project patterns in priority order. By the time someone asks who owns the spend, the answer is already on the data — filterable and groupable in the explorer.
Team plan and above
How it worksProduct examples are illustrative. Usage estimates and provider-reported costs are separate measures; availability varies by connected source.
Explore the data viewWhy is Databricks spend hard to control?
- Databricks spend moves with jobs, cluster sizing, SQL warehouse uptime, and model serving, and the bill is usage-based in DBUs. Most teams only look after spend has accumulated.
- DBU totals alone do not say what changed. Usage needs to be broken down by workspace, SKU, and product to see whether a job cluster, an always-on warehouse, or model serving drove the increase.
- Databricks usually sits beside cloud, data, and AI spend. Reviewing it separately hides the real infrastructure total — especially when the same workloads also drive AWS, Azure, or GCP compute charges.
Know what you are connecting.
The coverage
- StackSpend reads account-wide usage from system.billing.usage joined to USD list prices, using a read-only service principal and one small SQL warehouse.
- Jobs, all-purpose and serverless compute, SQL warehouses, DLT pipelines, and model serving appear in the same monitoring workflow as the rest of your providers, per workspace and SKU.
- Daily Slack or email signals, budget thresholds, anomaly detection, and pace-to-forecast make Databricks spend visible before the invoice closes.
The source
Billing and usage from your connected providers. Credential types and permission controls vary by provider.
Provider connection guidesThe limits
Provider reporting and scheduled sync determine freshness. Available history and attribution vary by source; review the setup guide for coverage. Alerts notify your team; they do not block requests or enforce a spending cap.
What we track
- Databricks billing system tables
- system.billing.usage and list_prices
- Account-wide DBU usage at USD list price
- Cost by workspace, SKU, and product
- Jobs, all-purpose, and serverless compute
- SQL warehouses, DLT, and model serving
- Budget thresholds and anomaly detection
- Forecasting
Who should use StackSpend for Databricks?
- Teams that want daily visibility into spend without manually checking billing portals.
- Buyers replacing spreadsheets and fragmented native dashboards with one monitoring workflow.
- Operators who need read-only setup, alerts, and forecasting before overrun becomes month-end reality.
Evaluation checklist
- 01
Start a trial
Open a StackSpend workspace with no credit card required.
- 02
Connect with read-only access
Use the setup guide to connect the provider or workflow with the minimum permissions needed.
- 03
Review the first 90 days
Check history, alerts, anomalies, and forecast so you can decide whether the workflow is worth adopting.
StackSpend alongside Databricks account console and usage dashboards.
Native tools provide provider-specific reporting and controls. StackSpend adds a shared monitoring workflow across connected sources.
Databricks account console and usage dashboards
- Usage dashboards are strong for investigation but still require someone to check them
- System-table rows need to be queried and interpreted before they become a daily workflow
- No unified view with AWS, GCP, Azure, Snowflake, or AI provider spend
- Budget pacing and anomaly response require a separate monitoring layer
StackSpend
- Daily Databricks cost signal delivered beside the rest of your cloud and AI stack
- DBU usage priced in USD and broken down by workspace, SKU, and product
- Anomaly detection catches job, warehouse, and serving spikes as they happen
- Forecasting and budget thresholds show month-end exposure before invoice time
What do you get when you connect Databricks?
- Setup time
- Most teams can connect and validate setup in about 5-10 minutes.
- Access model
- Read-only credentials only. StackSpend does not modify provider resources or billing settings.
- Signals
- Daily Slack or email updates, anomaly alerts, and budget tracking in one workflow.
- History and forecast
- Historical spend context plus pace-to-forecast so overruns are visible before month-end.
Check the details before connecting.
Review connection permissions
Read the provider setup guides before sharing credentials.
Provider setup guidesSee the security details
How credentials, tenant isolation and data handling work.
Security and data handlingTalk to the team
Ask about your stack or requirements before connecting.
Contact StackSpendAbout Andrew DayDatabricks Cost Monitoring, answered
What causes Databricks costs to spike?
- A scheduled job runs on an oversized or lingering cluster after a workload change
- A SQL warehouse stays running between queries instead of auto-stopping
- DLT pipelines or streaming workloads process more data after a new source lands
- Model serving or vector search endpoints stay provisioned after an experiment ends
What is StackSpend for Databricks Cost Monitoring?
StackSpend connects to the Databricks billing system tables (system.billing.usage and list_prices) through a SQL warehouse with a read-only service principal. Track account-wide DBU spend by workspace, SKU, and product — jobs, all-purpose and serverless compute, SQL warehouses, DLT, and model serving — alongside AWS, GCP, Azure, Snowflake, and AI providers.
Why do engineering-led teams use StackSpend for databricks cost monitoring?
Engineering-led teams use StackSpend for databricks cost monitoring to catch cost problems the day they start — not three weeks later when the invoice lands. StackSpend reads account-wide usage from system.billing.usage joined to USD list prices, using a read-only service principal and one small SQL warehouse. Jobs, all-purpose and serverless compute, SQL warehouses, DLT pipelines, and model serving appear in the same monitoring workflow as the rest of your providers, per workspace and SKU.
What Databricks Cost Monitoring data does StackSpend track?
StackSpend tracks: Databricks billing system tables, system.billing.usage and list_prices, Account-wide DBU usage at USD list price, Cost by workspace, SKU, and product, Jobs, all-purpose, and serverless compute, SQL warehouses, DLT, and model serving, Budget thresholds and anomaly detection, Forecasting. All data is pulled using read-only credentials — StackSpend never modifies your account or provider settings.
How do I connect Databricks Cost Monitoring to StackSpend?
Connection takes around 5–10 minutes. You grant read-only access and StackSpend handles the rest. The step-by-step setup guide is at /resources/guides/providers/databricks.
How is StackSpend different from Databricks Cost Monitoring's native billing dashboard?
Databricks Cost Monitoring's native billing dashboard is useful for investigation but requires you to log in to look. StackSpend delivers a daily cost signal to Slack or email, fires anomaly alerts the day a spike starts, and surfaces pace-to-forecast so overruns are visible before month-end.
Does StackSpend support multiple Databricks Cost Monitoring accounts?
Yes. StackSpend supports connecting multiple Databricks Cost Monitoring accounts or workspaces to the same organisation. All accounts roll up into a single combined view alongside your other providers.
For the current provider catalogue, see supported integrations.
Tomorrow morning: your Databricks number, in Slack.
Connect Databricks today and follow spend, budgets and alerts in one place. Review provider permissions before connecting.