​​A Time Series Database (TSDB) is a database optimized for time-stamped or time series data. Time series are simply measurements or events that are tracked, monitored, downsampled, and aggregated over time. This could be server metrics, application performance monitoring, network data, sensor data, events, clicks, trades in a market, and many other types of analytics data. The key difference with time series data from regular data is that you’re always asking questions about it over time.

The most popular solutions today are:

- InfluxDB (★ 14,629 on GitHub, written in Go)
- Graphite (★ 4,325 on GitHub, written in Python)
- Prometheus (★ 19,717 on GitHub, written in Go)
- DalmatinerDB (★ 674 on GitHub, written in Erlang)
- Heroic by Spotify (★ 674 on GitHub, written in Java)
- Akumuli (★ 538 on GitHub, written in C++)

In addition, recently the TimescaleDB 1.0 was announced.

- TimescaleDB (★ 5,898 on GitHub, is packaged as a PostgreSQL extension). TimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL, providing automatic partitioning across time and space (partitioning key), as well as full SQL support.

#tsdb #metrics #data #store

​​Grafterm - (★951) is the metrics dashboards on terminal (a grafana inspired terminal version).

#tui #terminal #go #metrics #dashboard