The time-series database that developers love.
Reliable, scalable, flexible.

TimescaleDB is the leading open-source relational 
database for time-series data. Built on PostgreSQL, 
so you get a rock‑solid, proven foundation.

Try for free

Instant productivity

  • Use full SQL for advanced time-series analysis, not a proprietary query language that’s hard to learn.
  • Integrate with anything in the Postgres ecosystem and your favorite open source projects.

Use full SQL for advanced time-series analysis, not a proprietary query language that’s hard to learn. Integrate with anything in the Postgres ecosystem and your favorite open source projects.

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The SQL vs. NoSQL difference

SELECT time, (memUsed / procTotal / 1000000) as value
FROM measurements
WHERE time > now() - '1 hour';

// Memory used (in bytes)
memUsed = from(bucket: "telegraf/autogen")
  |> range(start: -1h)
  |> filter(fn: (r) =>
    r._measurement == "mem" and
    r._field == "used"
  )
// Total processes running
procTotal = from(bucket: "telegraf/autogen")
  |> range(start: -1h)
  |> filter(fn: (r) =>
    r._measurement == "processes" and
    r._field == "total"
    )
// Join memory used with total processes and calculate
// the average memory (in MB) used for running processes.
join(
    tables: {mem:memUsed, proc:procTotal},
    on: ["_time", "_stop", "_start", "host"]
  )
  |> map(fn: (r) => ({
    _time: r._time,
    _value: (r._value_mem / r._value_proc) / 1000000
  })
)

Accelerated 
performance & reliability

  • Up to 7000x faster than InfluxDB for many queries.
  • Superior support for high cardinality workloads and 10x better resource utilization.

Up to 7000x faster than InfluxDB for many queries. Superior support for high cardinality workloads and 10x better resource utilization.

Liaka

InfluxDB was not scalable nor resource-efficient for our workload. Since we are huge fans of PostgreSQL, TimescaleDB was a natural solution. The transition allowed us to retire complex internal applications and immediately allowed us to correlate licensing data with farm usage.”

Mahlon Smith

Senior Technologist, LAIKA

Massive scale

  • Write millions of data points per second.
  • Store 100s of terabytes on a single node or petabytes across multiple nodes.

Write millions of data points per second. Store 100s of terabytes on a single node or petabytes across multiple nodes.

Relational & time-series, together

  • Use the relational data model that you already know.
  • Perform complex queries and build powerful applications faster.
  • Fully support 40+ datatypes, JOINs, foreign keys, and other powerful features.

Use the relational data model that you already know. Perform complex queries and build powerful applications faster.

Worry-free operations in the cloud of your choice

  • Timescale Cloud is available on AWS, Azure, and GCP, in over 75 regions around the world.
  • Influx Cloud is available in 4.

Timescale Cloud is available on AWS, Azure, and GCP, in over 75 regions around the world. Influx Cloud is available in 4.

Lower costs

  • Save on storage with 94% compression rates from best-in-class algorithms, and a more memory-efficient architecture than InfluxDB.
  • Choose from 2,000+ CPU and storage configurations.
  • Read more about compression

Save on storage with 94% compression rates from best-in-class algorithms. Choose from 2,000+ CPU and storage configurations.

Read more about compression

How does TimescaleDB stack up against InfluxDB?

Compare database performance, speed, user
experience, cost, and more at-a-glance.
TimescaleDB
InfluxDB
Database foundation
Built on PostgreSQL, a proven foundation for your data
Proprietary
License
Apache 2 OSI core + Source available, permissive, and free Timescale license
MIT License, Clustering available with paid Enterprise License only
Query language
Proprietary, FluxQL
Data model
Relational
time-series and business data together in one place
NoSQL
tag-set support for time-series data only
Ecosystem
Works with the entire PostgreSQL ecosystem
Limited
Query performance
Up to 7000x faster than InfluxDB, especially as cardinality increases
Competitive when cardinality of metric is small
Ingest speed
High (Millions of data points per second, even at high cardinality)
Moderate (Less than one million metrics per second at moderate cardinality)
Scale
Stores 100s of terabytes on a single node, or petabytes across multiple nodes
Clustering and multi-node only available with Enterprise
High availability
Broad PostgreSQL tooling for backup/restore, replication, and failover
Proprietary tooling for backup/restore. 
Clustering only available with Enterprise
Cloud cost
Charges based on compute and storage. No limitation on queries, ingest, or output Save on storage with 94% compression
Charges based on queries, ingest, output and storage
Cloud availability
2000+ compute and storage configurations across 75 regions
Limited configuration across 
5 US/EU regions

Ready to make the move to TimescaleDB?