Snowflake vs Databricks vs Google BigQuery

Snowflake is the independent multi-cloud SQL warehouse with the most mature data sharing and marketplace. Databricks is the unified lakehouse… See pricing, features & verdict.

Data Warehouses3-Way Comparison
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Quick Comparison

Snowflake

Best For:
Fully managed cloud data platform with elastic compute and storage separation
Architecture:
Cloud-native
Pricing Model:
Standard (1-10 users): $89/mo; Enterprise: custom
Ease of Use:
Moderate — standard setup and configuration
Scalability:
High — cloud-native auto-scaling
Community/Support:
Documentation and community forums

Databricks

Best For:
Unified analytics and AI platform with lakehouse architecture combining data lake and warehouse
Architecture:
Cloud-native
Pricing Model:
Standard $289/mo (5TB), Premium $1,499/mo (50TB)
Ease of Use:
Moderate — standard setup and configuration
Scalability:
Moderate — suited for teams and growing companies
Community/Support:
Documentation and community forums

Google BigQuery

Best For:
Serverless cloud data warehouse with pay-per-query pricing and deep GCP integration
Architecture:
Cloud-native
Pricing Model:
First 1 TB processed per month: free; $5/GB over 1 TB
Ease of Use:
Moderate — standard setup and configuration
Scalability:
High — built for enterprise workloads
Community/Support:
Commercial support included

Feature Comparison

Querying & Performance

SQL Support

Snowflake
Databricks⚠️
Google BigQuery

Real-time Analytics

Snowflake⚠️
Databricks⚠️
Google BigQuery

Scalability

Snowflake
Databricks⚠️
Google BigQuery

Platform & Integration

Multi-cloud Support

Snowflake⚠️
Databricks⚠️
Google BigQuery

Data Sharing

Snowflake⚠️
Databricks⚠️
Google BigQuery

Ecosystem & Integrations

Snowflake⚠️
Databricks
Google BigQuery

General

Documentation Quality

SnowflakeGood
DatabricksGood
Google BigQueryGood

API Availability

Snowflake
Databricks
Google BigQuery

Community Support

SnowflakeActive
DatabricksActive
Google BigQueryActive

Enterprise Support

Snowflake
Databricks
Google BigQuery

Legend:

Full support⚠️Partial / LimitedNot supported

Our Verdict

Snowflake is the independent multi-cloud SQL warehouse with the most mature data sharing and marketplace. Databricks is the unified lakehouse platform combining SQL analytics, data engineering, and ML on one platform. BigQuery is Google's serverless warehouse with zero cluster management and native GCP integration. Choose Snowflake for SQL-first analytics and multi-cloud, Databricks for unified data + ML workloads, BigQuery for serverless simplicity on GCP.

When to Choose Each

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Choose if:

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Choose if:

💡 This verdict is based on general use cases. Your specific requirements, existing tech stack, and team expertise should guide your final decision.

Frequently Asked Questions

Which is best for a startup?

BigQuery — serverless means zero infrastructure management, and on-demand pricing ($6.25/TB) means you only pay for queries. Snowflake is also good with per-second billing and auto-suspend. Databricks is better suited for teams that need both data engineering and ML.

Can Databricks replace Snowflake?

For SQL analytics, Databricks SQL is competitive but Snowflake is more mature. Databricks excels when you need data engineering (Spark), ML (MLflow), and SQL analytics on one platform. Many organizations use both — Databricks for data engineering/ML, Snowflake for BI/analytics.

Which is cheapest?

Depends on workload. BigQuery on-demand is cheapest for sporadic queries. Snowflake with commitment pricing is competitive for steady workloads. Databricks is typically most expensive but provides the broadest capabilities (data engineering + ML + SQL). All three offer significant discounts with reserved capacity.

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