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Databases · head to head

TimescaleDB vs turbopuffer

TimescaleDB logo

TimescaleDB

Databases

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

From
Free
Rated
-
Full reviewWebsite
turbopuffer logo

turbopuffer

Databases

Closed-source vector and full-text search service built directly on object storage, with cold queries measured in seconds rather than milliseconds.

From
$16/month
Rated
-
Full reviewWebsite

The short version

  • Only TimescaleDB has a free tier, so it costs nothing to try first.
  • Each has a real cost: TimescaleDB inherits PostgreSQL write path limitations, creating a ceiling on ingestion throughput; turbopuffer a cold namespace pays object storage latency on the first query, with a documented p90 around 1,214 ms on a million documents, so any interactive search box needs the data kept warm or the user waits about a second.
  • They diverge on capability: TimescaleDB covers Time-series Optimization, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which TimescaleDB and turbopuffer actually diverge.

Attributes where TimescaleDB and turbopuffer differ
AttributeTimescaleDBturbopuffer
Starting priceFree$16/month
Pricing modelUnknownsubscription
Free tierYesNo
PlatformsLinux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure)Web
Founded2012Unknown

Identical on both: user rating (Not yet rated), category (Databases).

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 turbopuffer

  • Object storage architecture
  • Namespaces
  • Vector search
  • Full-text search
  • Attribute filtering
  • Documented limits
  • Configurable consistency
  • Durable writes

What people use each for

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

TimescaleDB

  • Monitoringnot turbopuffer
  • IoT datanot turbopuffer
  • Financial datanot turbopuffer
  • Log analyticsnot turbopuffer
  • Observabilitynot turbopuffer

turbopuffer

  • A product with one search index per customer and thousands of customers, most of whose data is idle on any given daynot TimescaleDB
  • Very large corpora where holding every vector in memory is the dominant cost and occasional cold-query latency is acceptablenot TimescaleDB
  • Hybrid retrieval combining BM25 and vector search where running and synchronising two separate systems is the problem being solvednot TimescaleDB
  • Retrieval for agent and assistant products where indexes are created and destroyed frequently and per-index overhead must be near zeronot 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

turbopuffer

  • A cold namespace pays object storage latency on the first query, with a documented p90 around 1,214 ms on a million documents, so any interactive search box needs the data kept warm or the user waits about a second.
  • Queries are eventually consistent by default, and after roughly 128 MiB of outstanding writes new data is invisible until indexed, which the vendor puts at tens of seconds for small namespaces and tens of minutes for large ones, so a bulk re-index is not immediately queryable.
  • It is closed source with no community edition, so single-tenant or bring-your-own-cloud deployment is a commercial negotiation rather than a deployment choice, and there is no path to running it yourself if the relationship ends.
  • Per-namespace ceilings, roughly 10,000 writes per second, 32 MB/s and 500 million documents per shard, mean a single enormous index has to be sharded across namespaces by your application rather than by the service.
  • It is a search engine, not a database: there are no joins, no cross-document transactions and no SQL, so it sits beside a primary datastore and keeping the two in step is work that belongs to you.

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

turbopuffer

$16/month
  • Launch$16/month
    • All database features
    • Multi-tenancy deployment
    • SOC2 & GDPR-ready DPA
  • Scale$256/month
    • Everything in Launch
    • HIPAA-ready BAA
    • Single Sign-On (SSO)
  • Enterprise$4096/month
    • Everything in Scale
    • Single-tenancy & BYOC deployment options
    • Private networking

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 turbopuffer if

  • You need object storage architecture.
  • You also want namespaces.
turbopuffer review

Questions people ask

Is TimescaleDB or turbopuffer better?
Neither clearly leads. TimescaleDB starts at Free and turbopuffer at $16/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, TimescaleDB or turbopuffer?
TimescaleDB has a free tier; the other does not. Paid plans start at Free for TimescaleDB and $16/month for turbopuffer.
Does TimescaleDB or turbopuffer run on more platforms?
TimescaleDB runs on Linux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure). turbopuffer runs on Web.
Can I use TimescaleDB for free?
Yes. TimescaleDB has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
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 turbopuffer is typically brought in for.
What can TimescaleDB do that turbopuffer cannot?
TimescaleDB covers Time-series Optimization, PostgreSQL Extension, Automatic Partitioning, Continuous Aggregates. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

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
turbopuffer: Can I self-host turbopuffer?

There is no open source or community edition. Single-tenant and bring-your-own-cloud deployments exist as commercial arrangements, but there is no way to run it independently of the vendor.

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
turbopuffer: How fast is it really?

Warm queries perform comparably to in-memory search engines. Cold queries, where data is not cached, have a documented p90 around 1,214 ms on a million documents. Write p90 is around 248 ms for a 512 KB upsert because writes go straight to object storage.

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
turbopuffer: Is it consistent?

Eventually consistent by default, with the vendor reporting that over 99.8% of queries return consistent data. Strong consistency can be requested per query at a latency cost. Large write bursts have a longer visibility delay while indexing catches up.

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
turbopuffer: What is it best at?

Large numbers of namespaces where most are idle. The architecture makes cold data cheap to keep, which is exactly the shape of a multi-tenant product with a long tail of inactive customers.

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
turbopuffer: What are the hard limits?

Up to 128 billion documents and 256 TB per namespace, 500 million documents per shard, 64 MiB per document, 10,752 dense vector dimensions, roughly 10,000 writes per second per namespace and a maximum result set of 10,000.

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