Pricing comparison
Google BigQuery vs Microsoft Fabric
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 Microsoft Fabric pricing.
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Recorded starting rates: Google BigQuery Price unavailable; Microsoft Fabric 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.
Feature Comparison
| Feature | | |
|---|---|---|
| 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 |
| unified saas platform | Not recorded | Synapse Data Warehouse + Data Factory + Data Engineering + Data Science + Real-Time Analytics + Power BI + Industry Solutions |
| onelake unified storage | Not recorded | Single data lake for all workloads - Delta/Iceberg open formats |
| copilot ai assistance | Not recorded | Copilot capabilities subject to capacity, region and current feature eligibility |
| power bi native | Not recorded | Power BI integration; confirm capacity and user-license requirements separately |
| direct lake mode | Not recorded | Power BI queries directly against OneLake - no data movement |
| delta lake native | Not recorded | Open table format support |
| notebooks spark | Not recorded | Apache Spark managed runtime |
| eventstream | Not recorded | Real-time event processing |
| eventhouse | Not recorded | Real-time analytics database |
| data activator | Not recorded | No-code trigger engine |
| macc eligible | Not recorded | Azure Consumption Commitment eligible |
| pause resume | Not recorded | Pay-as-you-go capacity can be paused; storage, commitments and other charges need separate review |
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Dive Deeper
Google BigQuery
Microsoft Fabric
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:
Frequently Asked Questions
- How do Google BigQuery and Microsoft Fabric prices compare?
- Google BigQuery: Price unavailable. Microsoft Fabric: 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 Microsoft Fabric?
- 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.