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A high performance, high compression ratio, high usability open-source time-series database.

CnosDB English | 简体中文 An Open Source Time Series Database with high performance, high compression ratio and high playability. Features High batch writ
Information
Category: Golang / Miscellaneous
Watchers: 5
Star: 33
Fork: 9
Last update: Oct 31, 2021
Resource links
https://github.com/cnosdatabase/cnosdb

CnosDB

English | 简体中文

An Open Source Time Series Database with high performance, high compression ratio and high playability.

Features

  • High batch writing throughput.

  • High compression ratio.

  • Rich calculation algorithms.

Join the community

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.

Quick start

If you need a complete getting started guide, please check the Quickstart Guide

Construct

  1. Clone

    git clone https://github.com/cnosdatabase/cnosdb.git

  2. Compile

    go install ./...

Operation

  1. Start

    $GOPATH/bin/cnosdb

  2. Use

    $GOPATH/bin/cnosdb-cli

User's Guide

Create database

curl -i -XPOST http://localhost:8086/query --data-urlencode "q=CREATE DATABASE mydb"

Insert data

curl -i -XPOST 'http://localhost:8086/write?db=db' --data-binary 'cpu,host=server01,region=Beijing idle=0.72 1434055562000000000'

Query

curl -G 'http://localhost:8086/query?pretty=true' --data-urlencode "db=db" --data-urlencode "q=SELECT \"idle\" FROM \"cpu\" WHERE \"region\"='Beijing'"

How to contribute

Please refer to Contribution Guide to contribute to CnosDB.

License

MIT License

v0.9(Dec 28, 2021)

cnosdb-0.9_windows_amd64.zip

What's Changed

  • Influxql adaption https://github.com/cnosdatabase/cnosdb/pull/1
  • chore(*): Increase the packaging process by docker https://github.com/cnosdatabase/cnosdb/pull/4
  • refactor(*): Remove unnecessary content #15 https://github.com/cnosdatabase/cnosdb/pull/16

New Contributors

  • @zipper-meng made their first contribution in https://github.com/cnosdatabase/cnosdb/pull/1
  • @jcy20000106 made their first contribution in https://github.com/cnosdatabase/cnosdb/pull/12

Full Changelog: https://github.com/cnosdatabase/cnosdb/commits/v0.9

Contents

    inikep Lizard (formerly LZ5) is an efficient compressor with very fast decompression. It achieves compression ratio that is comparable to zip/zlib and zstd/brotli (at low and medium compression levels) at decompression speed of 1000 MB/s and faster.
    SiriDB SiriDB is a highly-scalable, robust and super fast time series database. Build from the ground up SiriDB uses a unique mechanism to operate without a global index and allows server resources to be added on the fly. SiriDB's unique query language includes dynamic grouping of time series for easy analysis over large amounts of time series.
    facebookarchive Beringei is a high performance, in-memory storage engine for time series data.
    chickenbestlover RNN based Time-series Anomaly detector model implemented in Pytorch.
    sgomes A tiny module to help preserve aspect ratio in pure CSS
    albertodeago vue-aspect-ratio - A tiny component to handle aspect ratios with no effort.
    NVlabs Programmable Neural Network Compression
    facebook Zstandard - Fast real-time compression algorithm
    nokia Time series data collector / exporter
    johannfaouzi A Python package for time series classification
    khiati-walid A Django | React application that forecast time series data using ARIMA and RNN models.
    amit1rrr Python package to compress numerical series into strings
    andybbruno TSXor: A Simple Time Series Compression Algorithm
    kei6u An effective time-series data compression/decompression method based on Facebook's Gorilla.
    RJT1990 Open source time series library for Python
    antirez Small strings compression library
    lz4 Extremely Fast Compression algorithm
    KarenUllrich A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).
    lz4 Extremely Fast Compression algorithm
    fab-jul PyTorch code for the CVPR'20 paper "Learning Better Lossless Compression Using Lossy Compression"
    DanielVZ96 Tzar: 👑Easy compression and extraction for any compression or archival format.
    Share this repo

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