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Transform your work with a time series database

Timescale is built to handle the scale and complexity of time series data to give you high performance, faster development, and lower storage costs.

Why use Timescale for my time series data?

Time series data is a sequence of data points collected over time intervals, allowing us to track how something changes over milliseconds, days, or even years. This feature-rich data does not simply include time as an aspect, but as a primary component of the data that helps developers analyze data and gather meaningful insights.

    Supercharge performance

  • Get 10-100x faster time series queries than vanilla PostgreSQL, InfluxDB, and MongoDB with automatic time-based partitioning and indexing. Give your users answers in milliseconds, not minutes with Timescale’s continuous aggregates.

    Build faster

  • Scale PostgreSQL for time series, events, and analytics with automatic time-based partitioning and indexing, incrementally-updated materialized views, columnar compression, and time series hyperfunctions.

    Scale efficiently

  • Get 90+% storage savings via columnar compression. Seamlessly tier data into consumption-based object storage, while still querying tiered data in SQL.
Why use Timescale for my time series data?

Who uses time series data?

Time series data can be found in a variety of sectors and industries, and is leveraged by companies large and small.

Our SmartCast Link appliance uses TimescaleDB to collect sensor readings from IoT-enabled lighting products. From our experience, TimescaleDB is uniquely positioned in the time-series database market as the only serious player that scales while natively supporting a robust, proven SQL engine.

Shane O'Donnell, IoT Data Architect at Cree
Get started with a purpose-built time series database.

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