Google BigQuery vs M3
Google BigQuery and M3 are both database software. Google BigQuery is a commercial product from Google. M3 is open source under Apache-2.0, with 4.9k GitHub stars.
Which to pick
- Pick Google BigQuery when
- You are on Google Cloud or export GA4 data and want SQL analytics without managing servers.
- Pick M3 when
- You run Prometheus at very large scale and need horizontally scalable long-term metrics storage.
Side by side
Google Cloud's serverless data warehouse for SQL analytics over very large datasets, with built-in ML and GA4 export.
Uber's metrics platform: a distributed time-series database, aggregator and query engine usable as long-term Prometheus storage and Graphite-compatible backend.
On-demand pricing charges per data scanned, so careless queries cost real money.
Complex to operate, and development has slowed; many teams choose Thanos, Mimir or VictoriaMetrics instead.
Production-ready
Usable
Cloud service
Self-hosted server
SQL
Go and etcd
Closed source, sold by Google
Open source, Apache-2.0 (permissive)
Closed source: you use it under the maker's terms and cannot change or resell the code.
You can build it into a product you sell, as long as you keep its copyright notice.
313 Wikipedia readers a month on phones
4.9k GitHub stars
Not known
Established: started 10 years ago, latest release v1.6.0.
Other comparisons
More databases
Both sides were judged on 2026-11-03 from makers' descriptions, Wikipedia, READMEs and GitHub data. License, age and popularity lines are worked out directly.