Databricks pricing guide details
Pricing Overview
Databricks uses a consumption-based pricing model built on Databricks Units (DBUs), a normalized measure of compute capacity. The catch: your bill has two layers. You pay Databricks for DBUs consumed per workload type, and you separately pay your cloud provider (AWS, Azure, or GCP) for the underlying VMs and storage. DBU rates range from $0.07/DBU for Model Serving to $0.70/DBU for Serverless SQL on AWS. Jobs Compute, the workhorse for production pipelines, costs $0.15/DBU. All-Purpose Compute for interactive notebooks jumps to $0.40/DBU. Databricks bills per second with no upfront costs on the on-demand plan. Free Edition replaced the Community Edition that Databricks retired in 2025. It costs nothing but is documented for non-commercial use only, is not covered by the support policy or SLA, and caps a workspace at one SQL warehouse of 2X-Small and five concurrent job tasks, so the 14-day trial with free credits is the route for evaluating a paid deployment. There is no traditional flat monthly subscription; every dollar ties back to actual compute consumption.
Plan Comparison
Databricks structures pricing around three subscription tiers that determine your per-DBU rate and available features. The table below shows DBU rates by compute type on AWS at the Standard tier baseline.
| Compute Type | DBU Rate (AWS) | Use Case | Notes |
|---|---|---|---|
| Jobs Compute | $0.15/DBU | Production pipelines | Most cost-efficient for batch |
| All-Purpose Compute | $0.40/DBU | Interactive notebooks | 2.7x that of Jobs |
| SQL Pro | $0.22/DBU | Classic SQL warehouses | BI workloads |
| Serverless SQL | $0.70/DBU | Managed SQL warehouses | Includes compute costs |
| Lakeflow pipelines | $0.20/DBU | Managed ETL | Declarative pipelines |
| Model Serving | $0.07/DBU | Foundation Model APIs | Cheapest per-DBU rate |
Premium tier adds 20-30% to these base rates but unlocks Unity Catalog, RBAC, audit logging, and table access controls. Enterprise tier is custom-priced and adds advanced security, compliance certifications, and dedicated support. We recommend Premium for any team running production workloads, as the governance features are essential once multiple teams share a workspace. Azure pricing runs 10-20% higher than AWS across all compute types, while GCP rates are similar to AWS. Standard tier is being discontinued on AWS and GCP, with Azure support ending in October 2026, so new deployments should plan for Premium or Enterprise from day one.
Hidden Costs and Considerations
The dual-billing structure is the biggest cost trap. Cloud infrastructure costs typically add 50-200% on top of your DBU charges. If Databricks quotes $1,000/month in DBUs, budget $2,000-$3,000 total. All-Purpose Compute clusters left running overnight burn money fast since per-second billing does not help if nobody terminates idle clusters. Serverless SQL at $0.70/DBU is the one exception where compute is included. Committed-use discounts of 20-40% require 1-3 year contracts negotiated directly with sales, and they lock you in.
Cost Estimates by Team Size
Based on published DBU rates and typical cloud infrastructure multipliers, here are realistic monthly cost estimates. The DBU portion represents roughly half your total bill; the rest goes to your cloud provider for VMs and storage.
| Team Size | Typical Workload | Estimated Total/Month | Breakdown |
|---|---|---|---|
| Startup (2-3 analysts) | 3 pipelines, light SQL | Depends on DBUs consumed | Jobs Compute + SQL Pro, minimal clusters |
| Mid-size (5-10 engineers) | Moderate ML, daily pipelines | Depends on DBUs consumed | Jobs + All-Purpose + SQL, Premium tier |
| Enterprise (20+ engineers) | Heavy ML, streaming, BI | Depends on DBUs consumed | All compute types, Premium or Enterprise |
These estimates assume on-demand pricing without committed-use discounts. Enterprise deals at $1M+ annual spend can achieve 30-50% below list rates. Spot instances on AWS or GCP can reduce cloud infrastructure costs by 60-80% for fault-tolerant batch workloads. Teams that aggressively use Jobs Compute instead of All-Purpose Compute and enable auto-termination on idle clusters can cut their bill by 40-60% compared to teams that rely on interactive clusters for everything.
How Databricks Pricing Compares
Databricks competes primarily with Snowflake for data platform spend, though the tools serve different primary audiences. We find Databricks wins on data engineering and ML cost-efficiency, while Snowflake is simpler for pure SQL analytics.
| Factor | Databricks | Snowflake | BigQuery |
|---|---|---|---|
| Pricing Model | DBUs + cloud infra | Credits ($2-$4/credit) | $7.50/TB scanned or slots |
| Best For | Engineering + ML | SQL analytics + BI | Ad-hoc SQL + Google ecosystem |
| Data Engineering | Native Spark | Snowpark (newer) | Dataflow/Dataproc |
| ML/AI | MLflow, Mosaic AI | Cortex (newer) | Gemini Enterprise Agent Platform (formerly Vertex AI) (separate) |
| Typical Annual Cost | $28K-$100K+ | $36K-$100K+ | Varies widely |
| Free Option | Free Edition (non-commercial use only) | Trial credits | 1 TB/month free queries |
For data engineering and ML workloads, Databricks is typically 15-30% cheaper than Snowflake because those workloads run natively on Spark rather than requiring translation layers. For SQL analytics, Snowflake delivers comparable or better price-performance with less operational overhead. BigQuery appeals to Google-native shops with its serverless model and per-TB pricing, though costs become unpredictable at high query volumes. Many organizations end up running Databricks and Snowflake side by side: Databricks for pipelines and ML, Snowflake for BI. The key distinction is that Databricks requires you to manage cloud infrastructure costs separately, adding operational complexity that Snowflake and BigQuery abstract away entirely.
Lakehouse//RT Beta pricing note
Lakehouse//RT is a separate Beta warehouse for low-latency, high-concurrency read serving. Databricks documents a temporary 30% reduction in Lakehouse//RT DBU consumption through January 31, 2027; Beta pricing and capabilities can change before general availability. This is a time-limited promotion, not a permanent platform rate, and it does not change the existing Databricks DBU figures on this page.