BigQuery

Google Cloud's serverless data warehouse — run SQL analytics on petabyte-scale datasets without managing infrastructure, with a generous free tier.

Best for: Data teams and analytics engineers on Google Cloud building data warehouses · organizations already in the Google Workspace ecosystem wanting native Sheets and Looker Studio integration · teams with variable query workloads where on-demand pricing is cheaper than provisioned alternatives

Free plan

4.5/5Editorial score 84/100cloud.google.com

Starts at

Free (10 GB storage, 1 TB queries/month)

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Editorial score84/100

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The editorial note

What to know about BigQuery

Google BigQuery is a fully managed, serverless cloud data warehouse that enables super-fast SQL analytics over massive datasets — scaling from gigabytes to petabytes without infrastructure management. BigQuery's on-demand pricing charges per query byte scanned, while flat-rate plans suit heavy analytical workloads. It's the backbone for many companies' data stack, integrating natively with Google Analytics, Ads, and Looker Studio.

Is it right for you?

Who BigQuery suits

Choose it if

Data teams and analytics engineers on Google Cloud building data warehouses
organizations already in the Google Workspace ecosystem wanting native Sheets and Looker Studio integration
teams with variable query workloads where on-demand pricing is cheaper than provisioned alternatives

Look elsewhere if

Teams outside the Google Cloud ecosystem — Snowflake or Amazon Redshift may integrate more naturally with AWS/Azure-first data stacks

What you get

Key features

Serverless SQL data warehouse
Columnar storage with automatic optimization
BigQuery ML for in-database machine learning
Streaming inserts for real-time analytics
Partitioned and clustered tables for cost optimization
Data sharing across organizations
Native integration with Looker Studio and Looker
Omni for multi-cloud query federation

Works with

Integrations9

Google Analytics 4Google Ads Looker StudiodbtFivetranAirbyteTableauPower BIVertex AI

What it costs

Pricing

BigQuery pricing plans
Plan	Price	What it includes
Free Tier	Free (10 GB storage, 1 TB queries/month)	10 GB free storage and 1 TB query processing per month
On-Demand	$6.25 per TB queried	Pay per query — $6.25 per TB of data processed
Capacity Compute	From $2,000 / month	Reserved compute slots for predictable workloads and lower cost

Prices are recorded from the vendor's public pricing page and can change. Check before you buy.

The trade-off

Pros and cons

Pros

Serverless — no infrastructure to manage, scales automatically
Blazing fast SQL queries on terabyte+ datasets in seconds
Deep Google ecosystem integration: Analytics, Ads, Looker, Vertex AI
BigQuery ML enables SQL-based machine learning without Python
Free tier includes 10GB storage and 1TB query processing per month

Cons

Query costs can spike unexpectedly on large tables without partition optimization
Steeper learning curve for teams new to cloud data warehouses
Joins across very large tables without proper optimization can be expensive
Data egress fees apply when moving data out of Google Cloud

Quick read

At a glance

Category: Development & Coding
Pricing model: Usage based
Entry plan: Free (10 GB storage, 1 TB queries/month)
Free plan: Available
Free trial: Not listed
Website: cloud.google.com

The verdict

Our take on BigQuery

BigQuery is one of the best data warehouses for teams on Google Cloud. The serverless model, generous free tier, and native Google Workspace integration make it the easiest path to a modern analytics stack for Google Cloud users. For AWS teams, Redshift Serverless provides a comparable serverless experience. Snowflake is the best choice for multi-cloud teams or those who need the most mature data sharing and marketplace features. For variable workloads, BigQuery's on-demand pricing often beats Snowflake's credit-based model.

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Editorial review

From the journal

Editorial review of BigQuery

By TopToolsPick Editorial

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