Netflix/atlas
Some data may be outdated — see provenance labels.
In-memory dimensional time series database. observed · 2026-09-23
Health v2 · maintenance only
86/100
- Activity 96
- Release rhythm 65
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: 7
- age_days: 4459
- days_rel: 235
- days_push: 29
- n_releases_24m: 4
Adoption not part of the score
3567 stars · 358 forks observed · 2026-09-23
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Atlas is Netflix's in-memory dimensional time series database, serving as a backend for storing and querying operational metrics at scale. It provides a query language and HTTP API for analyzing tagged time series data in real time.
Use cases
- store and query application metrics in memory
- run dimensional queries on tagged time series data
- build a monitoring backend for cloud infrastructure
- analyze operational metrics with a query API
- visualize time series data from dashboards
When to choose
- you need fast in-memory queries over high-cardinality tagged metrics
- you operate large-scale cloud infrastructure and need a metrics backend
- you want Netflix-proven time series storage with an expressive query language
When to avoid
- you need durable long-term disk-based storage of time series
- you want a lightweight single-node metrics store
- your stack is not JVM-friendly
Facets
service · maturity active
database monitoring analytics http-server monitoring analytics big-data time-series jvm self-hosted time-series-database metrics observability scala netflix dimensional-data devops web-server
1 source
- readme: https://github.com/Netflix/atlas · fetched 2026-09-23 · fba40296e870
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Netflix/atlas | main | 86 |
For agents
Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem