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An Open Source Distributed Time Series Database with high performance, high compression ratio and high usability.
Click to view roadmap
- Ultra-large data size
- Distributed support for more than 1 billion time series
- Support more than 100 billion data points storage
- Support distributed aggregation query under massive time series
- Fast batch writing
- Define new memory and disk data structure
- Hardware resource abstraction and write optimization
- Dynamic adjustment of node load to optimize performance under data skew
- Multi-level storage strategy to optimize back-end IO
- Ultra-high data compression ratio
- Column based storage
- Multi-level compression
- Type and distribution adaptive compression algorithms
- Comprehensive compression ratio over 60 times -Rich calculation functions
- More than 50 calculation functions
- Interface modular design
- Excellent ecosystem
- Native support for k8s and docker
- Support for Java, Go, C/C++, Python development interfaces
- Support for third-party tools such as Telegraf, Grafana, Prometheus, etc.
All developers/users who love time series databases are welcome to participate in the CnosDB User Group. Scan the QR code below and add CC to join the group.
Please check Instructions for joining the group beforehand.
If you need a complete getting started guide, please check the Quickstart Guide
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Clone
git clone https://github.com/cnosdb/cnosdb.git -
Compile
go install ./...
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Start
$GOPATH/bin/cnosdb -
Use
$GOPATH/bin/cnosdb-cli
curl -i -XPOST http://localhost:8086/query --data-urlencode "q=CREATE DATABASE mydb"
curl -i -XPOST 'http://localhost:8086/write?db=db' --data-binary 'cpu,host=server01,region=Beijing idle=0.72 1434055562000000000'
curl -G 'http://localhost:8086/query?pretty=true' --data-urlencode "db=db" --data-urlencode "q=SELECT \"idle\" FROM \"cpu\" WHERE \"region\"='Beijing'"
Please refer to Contribution Guide to contribute to CnosDB.
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Twitter: @CnosDB
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email: [email protected]