https://github.com/mattbostock/timbala

Durable time-series database that's API-compatible with Prometheus.
https://github.com/mattbostock/timbala

database prometheus promql time-series timeseries timeseries-database tsdb

Last synced: about 5 hours ago
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Durable time-series database that's API-compatible with Prometheus.

• Host: GitHub
• URL: https://github.com/mattbostock/timbala
• Owner: mattbostock
• License: apache-2.0
• Created: 2016-10-15T21:41:57.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2018-02-11T22:08:38.000Z (almost 7 years ago)
• Last Synced: 2024-06-20T15:26:31.373Z (5 months ago)
• Topics: database, prometheus, promql, time-series, timeseries, timeseries-database, tsdb
• Language: Go
• Homepage:
• Size: 43.7 MB
• Stars: 93
• Watchers: 8
• Forks: 4
• Open Issues: 48
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Code of conduct: docs/code_of_conduct.md
  • Security: docs/security.md

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README

        
[![Build Status](https://travis-ci.org/mattbostock/timbala.svg?branch=master)](https://travis-ci.org/mattbostock/timbala)

## Project status

Timbala is in a very early stage of development and is not yet production-ready. **Please do not use it yet for any data that you care about.**

There are several known issues that prevent any serious use of Timbala at this stage; please see the [MVP milestone](https://github.com/mattbostock/timbala/milestone/2) for details.

* * *



Timbala is a distributed, fault-tolerant time-series database intended to

provide durable long-term storage for multi-dimensional metrics.

It is designed to integrate easily with [Prometheus][], supports PromQL and is

API-compatible with Prometheus, but can be used standalone.

Data stored in Timbala can be visualised using [Grafana][] by

configuring a Prometheus data source pointing to Timbala.

[Prometheus]: https://prometheus.io/

[Grafana]: http://grafana.org/

## Design goals

### Ease of operation

- one server binary

- no external dependencies

- all nodes have the same role

- all nodes can serve read and write requests

### Fault-tolerant

- no single points of failure

- data is replicated and sharded across multiple nodes

- planned features for read repair and active anti-entropy

### Highly available

- high write throughput and availability