Fast and scalable timeseries database
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README.md

Sidewinder

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Sidewinder is a timeseries database designed for speed and scalability. It's purpose is to provide storage, retrieval and analysis for time series data generated over the last few days. It can be used to power dashboards and real-time correlations for time series data at scale.

What's new?

  • ANSI SQL / JDBC Server
  • Tag Key Value Index
  • Performance Improvements

Highlights

  1. Fast: ingest 2 million datapoints a second!
  2. Multi-purpose: store application metrics or IoT data
  3. Disk & Memory: store data in-memory or persist to disk

Features

Speed

Sidewinder uses either pure in-memory buffers or memory mapped disk storage providing fast reads and writes without any need for expensive disks.

Integrations

Provides integrations with collectd, influx etc.

SQL

Integrated with ANSI SQL and JDBC for easy data access

Grafana Support

Grafana is an industry defacto for dashboards and visualizations. Sidewinder has it's own Grafana datasource which once installed can be used to connect to the database for creating visualizations.

Downloads

Releases

Releases can be access through the Sidewinder releases page: https://github.com/srotya/sidewinder/releases

Jar

Sidewinder Jars can be found on Maven Central

Docker

Docker images are available docker pull srotya/sidewinder:latest

Install

http://sidewinder.srotya.com/docs/#/deployment/install

Docs

http://sidewinder.srotya.com/docs/

License

Sidewinder is licensed under Apache 2.0, Copyright 2017 Ambud Sharma and contains sources from other projects documented in the LICENSE file.