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TimescaleDB vs Apache Druid

TimescaleDB logo

TimescaleDB

Software

Time-series database built on PostgreSQL for real-time analytics

From
Free
Rated
-
Full reviewWebsite
Apache Druid logo

Apache Druid

Software

Real-time analytics database for sub-second OLAP queries

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: TimescaleDB inherits PostgreSQL write path limitations, creating a ceiling on ingestion throughput; Apache Druid open-source offering lacks high-availability, distributed architecture, and enterprise security features
  • They diverge on capability: TimescaleDB covers Time-series Optimization, Apache Druid covers Real-time Ingestion.

Where they differ

Only the attributes on which TimescaleDB and Apache Druid actually diverge.

Attributes where TimescaleDB and Apache Druid differ
AttributeTimescaleDBApache Druid
Pricing modelUnknownopen-source
PlatformsLinux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure)Docker, Kubernetes, Native deployment (Java-based)
Founded20121999

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in TimescaleDB

  • Time-series Optimization
  • PostgreSQL Extension
  • Automatic Partitioning
  • Continuous Aggregates
  • Native Compression
  • Full SQL Support
  • Real-time Analytics
  • PostgreSQL

Only in Apache Druid

  • Real-time Ingestion
  • Sub-second Queries
  • Column-oriented Storage
  • Streaming Integration
  • Approximate Algorithms
  • Flexible Schemas
  • Time-based Partitioning
  • Hadoop

Both cover

  • Kafka
  • Linux support
  • Docker support

What people use each for

The jobs each tool is most often brought in to do.

TimescaleDB

  • Monitoringnot Apache Druid
  • IoT datanot Apache Druid
  • Financial datanot Apache Druid
  • Log analyticsnot Apache Druid
  • Observabilitynot Apache Druid

Apache Druid

  • Real-time analytics platforms ingesting millions of events per second from streaming sourcesnot TimescaleDB
  • Applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows)not TimescaleDB
  • Time-series and event analysis at massive scale with columnar storage efficiencynot TimescaleDB

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

TimescaleDB

  • Inherits PostgreSQL write path limitations, creating a ceiling on ingestion throughput
  • Operational complexity increases significantly at scale, requiring expertise in chunk tuning and autovacuum management
  • Bloom filter indexes on compressed columns can return incorrect query results before upgrade
  • PostgreSQL 15 support ending June 2026, forcing mandatory upgrades to PostgreSQL 16 or later

Apache Druid

  • Open-source offering lacks high-availability, distributed architecture, and enterprise security features
  • Requires native integration with Apache Kafka or Amazon Kinesis for real-time ingestion; custom integrations need development
  • High-concurrency query support (hundreds of thousands QPS) requires significant cluster infrastructure investment

Pricing, plan by plan

TimescaleDB

Free
  • Open SourceFree
    • Self-hosted TimescaleDB
    • MIT-licensed core
    • Full PostgreSQL compatibility
  • Scale Plan (Cloud)$36/month
    • Compute and storage charges
    • Multi-node HA
    • Unlimited VPCs

Apache Druid

Free

No published plan breakdown. See the Apache Druid review.

Which should you pick?

Choose TimescaleDB if

  • You need time-series optimization.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure).
  • You also want postgresql extension.
TimescaleDB review

Choose Apache Druid if

  • You need real-time ingestion.
  • You want to start without paying.
  • You work on Docker, Kubernetes, Native deployment (Java-based).
  • You also want sub-second queries.
Apache Druid review

Questions people ask

Is TimescaleDB or Apache Druid better?
Neither clearly leads. TimescaleDB starts at Free and Apache Druid at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, TimescaleDB or Apache Druid?
TimescaleDB starts at Free and Apache Druid at Free.
Does TimescaleDB or Apache Druid run on more platforms?
TimescaleDB runs on Linux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure). Apache Druid runs on Docker, Kubernetes, Native deployment (Java-based).
Can I use TimescaleDB for free?
Both have a free tier, so you can try either at no cost before committing.
What is TimescaleDB best used for?
TimescaleDB is most often used for monitoring, iot data, financial data, log analytics. Of those, monitoring and iot data are not what Apache Druid is typically brought in for.
What can TimescaleDB do that Apache Druid cannot?
TimescaleDB covers Time-series Optimization, PostgreSQL Extension, Automatic Partitioning, Continuous Aggregates. Apache Druid covers Real-time Ingestion, Sub-second Queries, Column-oriented Storage, Streaming Integration. Both handle Kafka, Linux support, Docker support.

Answered from the vendors’ own pages

TimescaleDB: Is TimescaleDB free?

Yes. TimescaleDB is free and open source under the Timescale License. The managed cloud service offers a free trial with $1,000 in credits expiring in 30 days.

Source
TimescaleDB: What database does TimescaleDB run on top of?

TimescaleDB is a PostgreSQL extension that runs on top of PostgreSQL. You retain full PostgreSQL compatibility including SQL queries, transactions, and ecosystem tools.

Source
TimescaleDB: How much can TimescaleDB compress data?

TimescaleDB offers transparent columnar compression that can reduce storage by up to 95%. Newer data remains in row-oriented format for fast writes, while older data is automatically compressed to the column store.

Source
TimescaleDB: Does TimescaleDB require manual partitioning?

No. TimescaleDB handles automatic time-based partitioning through hypertables. Data is automatically chunked based on time intervals, requiring no manual partition management.

Source
TimescaleDB: What PostgreSQL versions does TimescaleDB support?

As of October 2025, TimescaleDB requires PostgreSQL 16 or greater. PostgreSQL 15 support will end with the June 2026 release, after which all instances must upgrade to PostgreSQL 16.

Source
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