Save space and money with compression

TimescaleDB provides 94-97% compression rates from best-in-class algorithms and other performance improvements.

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Store everything

To measure everything that matters, you need to collect and store everything that matters. Storage can be expensive and slow. You need compression.

You need TimescaleDB.

Efficiently compress your data to save storage, compute, and bandwidth.

TimescaleDB uses several time-series compression algorithms to help you mitigate storage needs. TimescaleDB compression gives you:

✅ 94 - 97% lossless compression rates

✅ Lower costs

✅ Better query performance

Store everything that matters so that you can measure everything that matters.

See compression in action

Benchmarking 200+ Billion Metrics in TimescaleDB with Compression and Actions

Developers ❤️ TimescaleDB

"Compression ratio is jaw-droppingly high :) When compressing a single hypertable in TimescaleDB, I received the following compression ratios:

  • Uncompressed hypertable: 1396 GB
  • Compressed hypertable: 77.0 GB
  • storage savings: 94%"

Tamihiro Lee, Network Engineer, SAKURA internet

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“For my use case, I’ve found TimescaleDB is a powerful and solid choice: it’s fast with reliable ingest rates, efficiently stores and compresses a huge dataset in a way that’s manageable and cost-effective, and gives me real-time aggregation functionality.”

Felipe Queis, senior engineer and TimescaleDB community member

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Get Started

Compression how-to guide

Follow our step-by-step guide to get up and running, from setting up compression for your environment to setting automated policies and getting the optimal compression ratio for your data.

Building columnar compression in a row-oriented database

Learn how we built compression to combine all of the benefits of PostgreSQL with additional query performance, see early benchmarks, and more.

Time-series compression algorithms, explained

Get a breakdown of various compression algorithms, including how they work, when and how you’d use them, how we’ve built them into TimescaleDB, and ways to get started.