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Google BigQuery vs Snowflake

BigQuery is truly serverless with nothing to size, on Google Cloud only; Snowflake runs on any major cloud and gives more control over compute sizing.

Side by side

Google BigQuery Snowflake
Vendor Google LLC (Google Cloud) Snowflake Inc.
Pricing model Usage-based Usage-based
Free tier Yes No
Deployment Cloud Cloud
Open source No No
Best for Teams already on Google Cloud who want a serverless warehouse with no cluster management. Teams wanting a fully managed, multi-cloud SQL warehouse with strong concurrency isolation and native data sharing.
Pricing

On-demand queries are billed per tebibyte scanned with 1 TiB free per month; capacity pricing bills per slot-hour by edition (Standard, Enterprise, Enterprise Plus); storage is billed separately per GiB, discounted after 90 days of inactivity.

On-demand queries $6.25 per TiB
Standard edition slots $0.04 per slot-hour
Enterprise edition slots $0.06 per slot-hour
Active logical storage $0.000031507 per GiB-hour

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Billed in per-second Snowflake credits whose price depends on edition (Standard, Enterprise, Business Critical, VPS), plus separate storage charges; a free trial is offered but there is no ongoing free tier.

Standard $2.00 per credit
Enterprise $3.00 per credit
Business Critical $4.00 per credit

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features
  • Serverless architecture with automatic compute allocation
  • On-demand (per-TiB) or capacity (per-slot) pricing models
  • BigQuery ML for in-warehouse model training via SQL
  • BI Engine in-memory acceleration for dashboards
  • BigQuery Omni for federated queries over other clouds
  • Native streaming ingestion via the Storage Write API
  • Materialized views and automatic query result caching
  • Fine-grained IAM, column-level security, and row-level access policies
  • Storage-compute separation with independently scalable virtual warehouses
  • Multi-cluster warehouses for concurrency scaling
  • Snowpark for Python, Java, and Scala pipelines
  • Native cross-account and cross-cloud data sharing
  • Time Travel and Fail-safe for data recovery
  • Automatic query optimization and result caching
  • Semi-structured data support (JSON, Avro, Parquet) via VARIANT
  • Support for external tables over cloud object storage

Verdict

Both are managed, usage-billed warehouses with no self-hosted option, but they differ in how much infrastructure decision-making they leave to you. Google BigQuery is serverless in the fullest sense: there is no warehouse size to pick for on-demand queries, Google allocates compute per query automatically, and pricing is either per byte scanned or per reserved slot. Snowflake asks you to size and manage virtual warehouses yourself — more control over cost and performance isolation per workload, at the cost of an extra decision every team has to learn to make well.

The other clear line is cloud availability: BigQuery runs only on Google Cloud, while Snowflake runs on AWS, Azure or Google Cloud, which matters if your organization is multi-cloud or wants that option later.

Choose Google BigQuery if

  • You are already on Google Cloud and want a warehouse with nothing to provision or size.
  • In-warehouse ML via SQL (BigQuery ML) or sub-second dashboard acceleration (BI Engine) are workloads you actually plan to use.
  • Predictable per-query, pay-per-byte-scanned billing suits your usage pattern better than a resizable compute unit.

Choose Snowflake if

  • You want the option to run on more than one cloud, now or later.
  • You want direct control over compute sizing per workload, with multiple independent virtual warehouses isolating teams from each other's query load.
  • Native cross-account data sharing with partners or other business units is a real requirement.

What they share

Both store data in a proprietary columnar format, both support semi-structured data natively (BigQuery via native JSON support, Snowflake via its VARIANT type), and both offer a genuine on-demand path to start without a long procurement cycle — BigQuery's free monthly scan allowance and Snowflake's free trial. Neither publishes a permanent free tier generous enough to run production workloads on indefinitely.

Last reviewed September 22, 2026

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