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Apache Pinot vs TimescaleDB

Apache Pinot logo

Apache Pinot

Software

Real-time distributed OLAP datastore for analytics

From
Free
Rated
-
Full reviewWebsite
TimescaleDB logo

TimescaleDB

Software

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

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Apache Pinot self-hosted and distributed, so running it means operating a cluster rather than consuming a service; TimescaleDB inherits PostgreSQL write path limitations, creating a ceiling on ingestion throughput
  • They diverge on capability: Apache Pinot covers Column-oriented, TimescaleDB covers Time-series Optimization.

Where they differ

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

Attributes where Apache Pinot and TimescaleDB differ
AttributeApache PinotTimescaleDB
Pricing modelopen-sourceUnknown
PlatformsLinux, Docker, KubernetesLinux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure)
Founded19992012

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 Apache Pinot

  • Column-oriented
  • Distributed Processing
  • SQL Support
  • Pluggable Indexing
  • Star-tree Index
  • Upsert Support
  • Spark
  • Presto

Only in TimescaleDB

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

Both cover

  • Real-time Analytics
  • Kafka
  • Linux support
  • Docker support

What people use each for

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

Apache Pinot

  • Sub-second analytics queries on freshly ingested datanot TimescaleDB
  • User-facing dashboards inside a productnot TimescaleDB
  • Real-time metrics at high ingest ratesnot TimescaleDB
  • Petabyte-scale analytics as run at LinkedIn and Ubernot TimescaleDB

TimescaleDB

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

Where each one falls short

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

Apache Pinot

  • Self-hosted and distributed, so running it means operating a cluster rather than consuming a service
  • Managed hosting comes from third parties such as StarTree rather than from the project
  • Built for user-facing real-time OLAP, so it is not a general purpose database

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

Pricing, plan by plan

Apache Pinot

Free
  • Open SourceFree
    • Real-time analytics
    • SQL queries
    • Horizontal scaling

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

Which should you pick?

Choose Apache Pinot if

  • You need column-oriented.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want distributed processing.
Apache Pinot review

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

Questions people ask

Is Apache Pinot or TimescaleDB better?
Neither clearly leads. Apache Pinot starts at Free and TimescaleDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Pinot or TimescaleDB?
Apache Pinot starts at Free and TimescaleDB at Free.
Does Apache Pinot or TimescaleDB run on more platforms?
Apache Pinot runs on Linux, Docker, Kubernetes. TimescaleDB runs on Linux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure).
Can I use Apache Pinot for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Pinot best used for?
Apache Pinot is most often used for sub-second analytics queries on freshly ingested data, user-facing dashboards inside a product, real-time metrics at high ingest rates, petabyte-scale analytics as run at linkedin and uber. Of those, sub-second analytics queries on freshly ingested data and user-facing dashboards inside a product are not what TimescaleDB is typically brought in for.
What can Apache Pinot do that TimescaleDB cannot?
Apache Pinot covers Column-oriented, Distributed Processing, SQL Support, Pluggable Indexing. TimescaleDB covers Time-series Optimization, PostgreSQL Extension, Automatic Partitioning, Continuous Aggregates. Both handle Real-time Analytics, 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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