# cnosdb/cnosdb

A cloud-native open source distributed time series database with high performance, high compression ratio and high availability.

Repository: https://github.com/cnosdb/cnosdb
Canonical: https://ross.abutalabs.com/products/cnosdb
Homepage: https://www.cnosdb.com
Language: Rust
License: AGPL-3.0
License Family: copyleft
Topics: database, time-series-database, distributed-database, sql, rust, rust-lang, time-series, timeseries
Last push: 2025-09-26T07:27:53+00:00

## Health v2 (maintenance only)
Score: 53/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 44, release rhythm 37, longevity 100
- inputs: {"age_days": 1773, "days_push": 341, "days_rel": 341, "gap_med": 42, "n_releases_24m": 6}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1756, forks 313 (observed 2026-08-28T04:05:32.190694+00:00)

## What it is
CnosDB is an open-source, cloud-native distributed time-series database written in Rust, supporting standard SQL, schemaless writes, and out-of-order historical data ingestion. It features native distributed design with data sharding, elastic scaling, and multi-tenancy, targeting IoT, industrial internet, connected vehicles, and IT operations workloads.

## Use cases
- store and query IoT sensor telemetry at scale
- ingest high-volume metrics from industrial equipment
- monitor IT infrastructure and operations metrics
- run SQL aggregate queries over time-series data
- handle out-of-order and historical data backfill
- deploy a scalable time-series database on Kubernetes
- store connected vehicle telemetry data

## When to choose
- you need a distributed, cloud-native time-series database with SQL support
- your workload is write-heavy with high compression requirements
- you need schemaless ingestion and out-of-order writes
- you want an open-source alternative to InfluxDB or TimescaleDB
- you need multi-tenant role-based access on time-series data

## When to avoid
- you need full ACID transactional workloads
- you require a permissive license (AGPL-3.0 may restrict commercial embedding)
- your data is relational rather than time-series
- you need a mature ecosystem with long-term enterprise support

## Facets
- artifact type: service
- maturity: active
- function: database, search-engine, analytics
- domain: databases, time-series, iot, big-data, cloud-computing
- platform: windows, self-hosted, cloud, rust
- tags: time-series-database, distributed-database, sql, cloud-native, olap, schemaless-writes, high-compression, linux, macos, docker, kubernetes

## Member repositories
- cnosdb/cnosdb (main) score 53

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:32.190694+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:27:51.467590+00:00, confidence not recorded.
  - readme: https://github.com/cnosdb/cnosdb (fetched 2026-08-28T04:05:32.190694+00:00, sha 6846def5a722)
  - homepage: https://www.cnosdb.com (fetched 2026-08-29T11:06:04.193246+00:00, sha 6b84af1c1bab)
  - site_page: https://docs.cnosdb.com (fetched 2026-08-29T11:06:04.196458+00:00, sha e3e78bed1ab3)
  - site_page: https://www.cnosdb.com/download (fetched 2026-08-29T11:06:04.198403+00:00, sha bd96dfe33404)
- Data as of 2026-08-30T08:39:29.467469+00:00.