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What is a Time Series Database?

Time-series data is simply data with a timestamp collected with the intent of tracking changes over time. A time-series database is a database system designed to store and retrieve such data for each point in time. Timestamped data can include data generated at regular intervals as well as data generated at unpredictable intervals.

A sample time-series data-metrics format.

When to use a time-series database

  • When your application needs data that accumulates quickly and your other databases are not designed to handle that scale.
  • For financial or industrial applications.
  • When your application needs to perform real-time analysis of billions of records.
  • When your application needs to perform online queries at millisecond timescales, and support CPU-efficient ad-hoc queries.

Use cases for time-series databases

  • Monitoring software systems and bare-metal hardware systems.
  • Continually capturing metrics from internet of things (IoT) devices.
  • Financial trading systems.
  • Recording stock prices over time.
  • Asset-tracking applications.


The RedisTimeSeries module simplifies the use of Redis for time-series use cases like IoT data, stock prices, and telemetry. With RedisTimeSeries, you can ingest and query millions of samples and events at the speed of Redis. It supports a variety of queries for visualization and monitoring with built-in connectors to popular monitoring tools like Grafana, Prometheus, and Telegraf.

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