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Pricing snapshot Dataset dated 2026-04-21

Pricing comparison

Google BigQuery vs Databricks

Side-by-side pricing breakdown for Data Warehouse & Analytics Engine decision-makers

Each amount uses its recorded currency; no currency conversion is applied. Confirm billing units, commitments, and current regional terms.

Compare the plan that fits your requirements

Check billing units, included usage and renewal terms. Starting prices alone do not establish an overall winner.

Dataset dated 2026-04-21. Sources: Google BigQuery pricing and Databricks pricing.

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Recorded starting rates: Google BigQuery Price unavailable; Databricks Price unavailable. Billing units and commitments can differ. Compare the plans that include your required features, then request quotes for the same quantity and term.

Google BigQuery logo

Google BigQuery

11 plans
Price unavailable
Free plan
Renewal Not recorded Not recorded
Visit Google BigQuery
VS
Databricks logo

Databricks

8 plans
Price unavailable
Renewal Not recorded Not recorded
Visit Databricks

Feature Comparison

Feature Google BigQuery Databricks
serverless architecture No infrastructure management Not recorded
auto scaling Automatic with on-demand or slots Not recorded
sql standard ANSI-compliant SQL Not recorded
bigquery ml In-SQL machine learning Not recorded
gemini integration Google Gemini in BigQuery Not recorded
iceberg support Open table format support Not recorded
partition cluster Reduces scanned data Not recorded
query caching Cached results free Not recorded
free tier 10 gib storage First 10 GiB per month free Not recorded
free tier 1 tib query First 1 TiB scanned per month free Not recorded
batch loading free Via shared pool Not recorded
data egress free intra region Within same Google Cloud region Not recorded
apache spark Not recorded Managed Spark runtime across all plans
delta lake Not recorded Open table format with ACID transactions
unity catalog Not recorded Premium+ - unified governance across data, AI, and file access
mlflow Not recorded All plans - ML lifecycle management
mosaic ai Not recorded AI/ML platform with vector search, RAG, fine-tuning
databricks sql Not recorded SQL warehouse for BI workloads
notebooks Not recorded Collaborative Python/Scala/SQL/R
workflows Not recorded Job orchestration
auto scaling clusters Not recorded All plans
photon engine Not recorded Vectorized query engine for SQL + Delta
ai agents Not recorded Databricks AI Agent framework
rbac audit logs Not recorded Premium+
customer managed keys Not recorded Enterprise
hipaa pci dss Not recorded Not assessed by StackScored; verify scope, vendor terms, and your obligations.
private link Not recorded Enterprise
multi cloud Not recorded AWS + Azure + GCP
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Dive Deeper

About the data warehouse & analytics engine category

Warehouse costs depend on workload as well as platform. BigQuery offers scanned-data and capacity pricing; Snowflake uses credits plus storage; Databricks meters different compute products in DBUs; Redshift offers provisioned and serverless compute; Fabric uses capacity SKUs with separate storage and licensing considerations. These units are not interchangeable monthly subscriptions. Compare a defined workload in the same region, including storage, ingestion, transfer and any commitment.

How to choose between data warehouse & analytics engine options

Start with data location, query frequency, concurrency and the engineering work you need. Test representative SQL queries, pipelines and any ML jobs on a realistic dataset. Measure elapsed time and billable usage together rather than comparing a credit, slot-hour, DBU or RPU in isolation. Check identity, governance, recovery and integration requirements against the exact edition and region. Include the cost of moving data and maintaining pipelines in the comparison.

Building Your Business Stack?

Decision-makers comparing tools often need more than one category. Here are related comparisons:

← See all Data Warehouse & Analytics Engine pricing

Frequently Asked Questions

How do Google BigQuery and Databricks prices compare?
Google BigQuery: Price unavailable. Databricks: Price unavailable. These are recorded starting prices; compare billing units, included usage and contract terms before treating them as equivalent costs.
Which is better for my requirements, Google BigQuery or Databricks?
Compare the recorded features and plan limits against your requirements, then confirm them with each vendor. This page does not establish hands-on testing or an overall winner.
What happens after the first billing term?
Use any recorded renewal rate as a dated observation. When a future rate is missing, ask the vendor; do not assume the starting price remains unchanged.