Prometheus vs TimescaleDB
On the evidence we track, Prometheus leads this comparison with a composite score of 69/100. 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.
Prometheus
LeaderA systems monitoring platform that collects metrics from configured targets at regular intervals, evaluates alert rules using PromQL, and triggers notifications. It uses a dimensional data model with key-value labels for flexible metric analysis and dashboarding.
TimescaleDB
TimescaleDB 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
Open 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.
Prometheus
Leader- Amazon SNS
- Discord
- incident.io
- Jira
- Mattermost
- Microsoft Teams
- OpsGenie
- PagerDuty
- Pushover
- Rocket.Chat
- Slack
- Telegram
- VictorOps
- Webex
- Webhook
TimescaleDB
- 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.