M3DB vs TimescaleDB
On the evidence we track, TimescaleDB leads this comparison with a composite score of 55/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for time-series databases. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
M3DB
M3 is a metrics platform consisting of a distributed time-series database, query engine, and ingestion system designed to handle massive metric volumes efficiently. It provides Prometheus and Graphite compatibility while optimizing for performance and cost efficiency through purpose-built storage and querying components.
TimescaleDB
LeaderTimescaleDB is a PostgreSQL extension designed to handle machine data and time-series workloads at scale, enabling operational databases for IoT platforms and physical-world monitoring.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
TimescaleDB
LeaderOpen source core; Cloud managed and Enterprise self-hosted options available; contact sales for pricing details
- Cloud Basic SupportFree
- Email support
- General questions
- Best practices guidance
- Cloud Production SupportContact sales
- 24x7 support for Severity 1-2
- 1h response for critical issues
- Support portal access
- On-call assistance
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
M3DB
- Prometheus
- Graphite
- Kubernetes
- Docker
TimescaleDB
Leader- Kafka
- S3
- Iceberg
- AWS
- Azure
- Observability tools
- Postgres ecosystem
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.