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Top time-series databases

22 time-series database software ranked by rating, review volume and listing quality.

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What to look for in time-series databases

The best choice depends on your workload, your team and your budget, not only on where an engine sits in this list. Before you shortlist the top-ranked time-series databases, check:

  • Ingestion rate: how many points a second it will take on the hardware or plan you can afford
  • Query language: SQL, PromQL, InfluxQL or another, and which your tools speak
  • Retention, downsampling and compression, which decide what long-term storage costs
  • High cardinality (many series) without a collapse in performance
  • Integrations with your monitoring, IoT or market-data pipeline
  • Self-hosted and managed options, and the licence of each

How to use this ranking

Use it to build a shortlist. Read each engine’s profile for its licence, deployment options and latest release, then test the two or three that fit on your own data and queries before you commit.

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  1. I

    InfluxDB

    DataBase

    InfluxDB is a time-series database for metrics, events and sensor data, with an open-source Core and commercial Enterprise and cloud editions.

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  2. TT

    TimescaleDB (Tiger Data)

    DataBase

    TimescaleDB is a PostgreSQL extension that adds time-series storage, partitioning and compression, sold as the managed Tiger Cloud service.

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  3. Q

    QuestDB

    DataBase

    QuestDB is an open-source time-series database using SQL with time-series extensions such as SAMPLE BY and ASOF JOIN, aimed at high-ingest workloads.

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  4. P

    Prometheus

    DataBase

    Prometheus is an open-source monitoring system with a built-in time-series database and the PromQL query language, used for infrastructure and application metrics.

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  5. V

    VictoriaMetrics

    DataBase

    VictoriaMetrics is an open-source time-series database and monitoring backend compatible with Prometheus protocols, in single-node and cluster forms.

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  6. AI

    Apache IoTDB

    DataBase

    Apache IoTDB is an open-source time-series database from the Apache Software Foundation, designed for IoT and industrial data.

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  7. T

    TDengine

    DataBase

    TDengine is a time-series database for IoT and industrial data, with stream processing and analytics components, sold self-hosted or as cloud.

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  8. G

    GreptimeDB

    DataBase

    GreptimeDB is an open-source, cloud-native time-series database for metrics, logs and events, supporting OpenTelemetry, Prometheus and InfluxDB protocols.

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  9. AD

    Azure Data Explorer

    DataBase

    Azure Data Explorer is a Microsoft managed analytics service for log, telemetry and time-series data, queried with Kusto Query Language and T-SQL.

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  10. K

    kdb+

    DataBase

    kdb+ is a proprietary time-series database from KX with the q vector language, combining in-memory and historical data for trading and real-time analytics.

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  11. C

    CrateDB

    DataBase

    CrateDB is a distributed SQL database for time-series, document and search workloads, available self-managed or as a cloud service.

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How is this ranking of time-series databases worked out?

A position here is earned, never bought. It is worked out from what each listing documents and what has been verified about it: a complete, accurate profile, and the checks a vendor has passed. Client reviews count where they exist, but they are still rare across this catalogue, so today the order comes mainly from documentation and verification. A top position means best-documented, not best for your workload.

Is the top-ranked engine the best for everyone?

No. Workloads, scale, skills and budgets differ, and so does the right engine. Use the checklist above and test before you choose.

Can a vendor pay to move up?

No. Sponsored and Featured places are labelled and shown apart from the ranked list, and they never change an engine’s position in it. How rankings work

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