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Google BigQuery vs Snowflake

Google BigQuery: Google's serverless, pay-per-query data warehouse built on Dremel and Colossus. Snowflake: Fully managed cloud data warehouse with separate storage and compute, now spanning AI and apps.

key differences

  • Only Google BigQuery has ttl / expiry.
  • Only Snowflake has branching.

choose google-bigquery for

  • +Cloud data warehouse on GCP
  • +Marketing and product analytics (GA4 export)
  • +Log and event analytics
  • +Ad-hoc exploration of very large datasets

best at · Warehouse, OLAP, Lakehouse

choose snowflake for

  • +Enterprise data warehouse
  • +ELT pipelines with dbt
  • +Cross-company data sharing
  • +BI and reporting at scale

best at · Warehouse, OLAP, Lakehouse

Google BigQueryGoogle's serverless, pay-per-query data warehouse built on Dremel and Colossus.
SnowflakeFully managed cloud data warehouse with separate storage and compute, now spanning AI and apps.
overview
Primary model
Columnar / OLAP
Columnar / OLAP
Also supports
Relational, Document, Vector, Spatial
Relational, Document, Vector, Spatial
Type
Managed service
Managed service
Status
Active
Active
Developer
Google
Snowflake Inc.
First release
2010
2014
Latest version
–
–
License
ProprietaryProprietary
ProprietaryProprietary
Free tier
✓
—
popularity
WhichDB Score
65.3
74.4
Rank
#12
#7
GitHub stars
–
–
Stack Overflow questions
26.1K
12.2K
scale & guarantees
Comfortable data size
Massive (Multi-PB)
Massive (Multi-PB)
Horizontal scaling
Native
Native
Multi-region
Read replicas
Read replicas
ACID
Full
Full
Consistency
Strong
Strong
Schema
Flexible
Flexible
Architecture
Serverless, Distributed, Shared storage
Distributed, Shared storage, Serverless
deployment
Self-hosted
—
—
Vendor-managed cloud
✓
✓
Serverless
✓
✓
Embedded
—
—
Edge
—
—
Clouds
Google Cloud
AWS, Azure, Google Cloud
capabilities
Transactions
✓
✓
Joins
✓
✓
Secondary indexes
—
—
Full-text search
✓
✓
Vector search
✓
✓
Geospatial
✓
✓
JSON
✓
✓
Change data capture
✓
✓
Triggers
—
—
Stored procedures
✓
✓
Materialized views
✓
✓
TTL / expiry
✓
—
Pub/Sub
—
—
Columnar storage
✓
✓
In-memory
—
—
Durable persistence
✓
✓
Compression
✓
✓
Encryption at rest
✓
✓
Role-based access
✓
✓
Time travel
✓
✓
Branching
—
✓
Online schema changes
✓
✓
Streaming ingest
✓
✓
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
GoogleSQL, Legacy SQL, Python (BigQuery DataFrames)
SQL, Snowflake Scripting, Python (Snowpark), JavaScript
Client languages
Python, Java, Go, JavaScript, C#, Ruby, PHP
Python, Java, JavaScript, Go, .NET, C, PHP
Best for
Warehouse, OLAP, Lakehouse, Real-time analytics
Warehouse, OLAP, Lakehouse
Add more to this comparisonNot sure either fits? Try smart match

Google BigQuery vs Snowflake: FAQ

What is the difference between Google BigQuery and Snowflake?

Google BigQuery: Google's serverless, pay-per-query data warehouse built on Dremel and Colossus. Snowflake: Fully managed cloud data warehouse with separate storage and compute, now spanning AI and apps. Only Google BigQuery has ttl / expiry. Only Snowflake has branching.

When should I choose Google BigQuery over Snowflake?

Choose Google BigQuery for cloud data warehouse on GCP; marketing and product analytics (GA4 export); and log and event analytics. Choose Snowflake for enterprise data warehouse, ELT pipelines with dbt and cross-company data sharing.

Is Google BigQuery or Snowflake more popular?

Snowflake ranks #7 on the WhichDB Score (74.4/100) and Google BigQuery ranks #12 (65.3/100). Popularity is not fit: check the requirements that matter for your project.

Are Google BigQuery and Snowflake open source?

No. Google BigQuery is proprietary, closed-source software. No. Snowflake is proprietary, closed-source software.