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InfluxDB vs TimescaleDB

InfluxDB is a purpose-built time-series engine; TimescaleDB is PostgreSQL with time-series performance added. The choice turns on relational joins.

Side by side

InfluxDB TimescaleDB
Vendor InfluxData, Inc. Tiger Data, Inc. (formerly Timescale)
Pricing model Free tier + paid plans Free tier + paid plans
Free tier Yes Yes
Deployment Cloud, Self-hosted Cloud, Self-hosted
Open source Yes (MIT) Yes (Apache-2.0)
Best for Teams building infrastructure, IoT or sensor monitoring systems that need a database purpose-built for time series. Teams already on PostgreSQL who need time-series performance without adopting a separate database.
Pricing

Core is free and self-hosted; Enterprise and the managed Cloud Dedicated tier are custom-priced, and Cloud Serverless is metered by ingestion, query and storage usage with a starting free credit.

Core (OSS) Free
Cloud Serverless Usage-based
Enterprise / Cloud Dedicated Custom pricing

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

The self-hosted extension is free; the managed Tiger Cloud service starts at a flat monthly rate and scales with compute/memory, with a custom-priced Enterprise tier.

Performance From $30/month
Scale From $36/month
Enterprise Custom pricing

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features
  • Columnar time-series storage on Arrow/Parquet
  • SQL and InfluxQL query support
  • High-throughput write ingestion
  • Built-in retention policies and downsampling
  • Telegraf agent for metrics collection
  • High availability and read replicas (Enterprise/Cloud Dedicated)
  • Automatic time-based partitioning (hypertables)
  • Native compression for time-series columns
  • Continuous aggregates (materialized rollups)
  • Full PostgreSQL SQL compatibility and joins
  • High availability and read replicas (Tiger Cloud)
  • Point-in-time recovery

Verdict

The decisive question is whether you want a purpose-built time-series engine or full PostgreSQL with time-series capability layered on. InfluxDB is built from the ground up around time-series ingestion and querying — the current InfluxDB 3 line runs on a columnar Arrow/Parquet engine, queryable in SQL and InfluxQL. TimescaleDB is PostgreSQL itself, with automatic time-based partitioning ("hypertables"), compression and continuous aggregates added on top, which means you keep full relational joins, existing Postgres drivers, ORMs and operational tooling that InfluxDB simply doesn't offer.

Choose InfluxDB if

  • Your workload is close to pure time series — metrics, IoT or sensor data — with limited need for relational joins against other tables.
  • You want the Telegraf agent ecosystem for collection, which is widely used and well documented.
  • You're comfortable with SQL or InfluxQL on the current v3 architecture.

Choose TimescaleDB if

  • You're already running PostgreSQL and want to add time-series performance without adopting a separate database.
  • You need relational joins between time-series data and normal business tables in the same query.
  • You want to keep existing Postgres drivers, ORMs and operational tooling rather than learning a new ecosystem.

What they share

Both offer a genuinely free, open-source, self-hosted core alongside a separately sold managed cloud service, both are freemium-priced, both integrate with Grafana, and both are commonly evaluated against each other for exactly this reason.

The honest caveat

InfluxDB's query language has shifted more than once — Flux was introduced in version 2 and is now deprecated in favor of SQL and InfluxQL in version 3 — so check which version any tutorial, driver or integration you find was written for before assuming it applies. TimescaleDB's parent company was also renamed, from Timescale to Tiger Data, with its managed offering now branded Tiger Cloud, which can cause confusion when comparing older pricing pages against current ones.

Last reviewed September 22, 2026

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