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Databases · head to head

NATS vs turbopuffer

NATS logo

NATS

Databases

High-performance messaging system for cloud-native applications

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 NATS has a free tier, so it costs nothing to try first.
  • Each has a real cost: NATS core NATS has no persistence at all, so messages are lost if no subscriber is listening; 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: NATS covers Very low latency, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which NATS and turbopuffer actually diverge.

Attributes where NATS and turbopuffer differ
AttributeNATSturbopuffer
Starting priceFree$16/month
Pricing modelOpen source, no licence feesubscription
Free tierYesNo
PlatformsLinux, macOS, Windows, Docker, KubernetesWeb

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 NATS

  • Very low latency
  • JetStream
  • Single binary
  • Request-reply

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.

NATS

  • Service-to-service messaging where latency is the binding constraintnot turbopuffer
  • Edge and IoT messaging where a lightweight broker mattersnot turbopuffer
  • Replacing a heavier broker when the workload does not need its guaranteesnot turbopuffer

turbopuffer

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

Where each one falls short

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

NATS

  • Core NATS has no persistence at all, so messages are lost if no subscriber is listening
  • JetStream adds the durability but also the operational complexity NATS is chosen to avoid
  • A much smaller ecosystem than Kafka or RabbitMQ, with fewer connectors and integrations
  • Fewer people know it, so hiring and existing organisational knowledge favour the alternatives

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

NATS

Free
  • NATSFree
    • Full functionality
    • No usage limits
    • Community support

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 NATS if

  • You need very low latency.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes.
  • You also want jetstream.
NATS review

Choose turbopuffer if

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

Questions people ask

Is NATS or turbopuffer better?
Neither clearly leads. NATS 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, NATS or turbopuffer?
NATS has a free tier; the other does not. Paid plans start at Free for NATS and $16/month for turbopuffer.
Does NATS or turbopuffer run on more platforms?
NATS runs on Linux, macOS, Windows, Docker, Kubernetes. turbopuffer runs on Web.
Can I use NATS for free?
Yes. NATS has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is NATS best used for?
NATS is most often used for service-to-service messaging where latency is the binding constraint, edge and iot messaging where a lightweight broker matters, replacing a heavier broker when the workload does not need its guarantees. Of those, service-to-service messaging where latency is the binding constraint and edge and iot messaging where a lightweight broker matters are not what turbopuffer is typically brought in for.
What can NATS do that turbopuffer cannot?
NATS covers Very low latency, JetStream, Single binary, Request-reply. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

Answered from the vendors’ own pages

NATS: Is NATS free?

Yes, open source and CNCF-graduated. Synadia sells a managed service.

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.

NATS: Does NATS persist messages?

Core NATS does not — it is fire-and-forget. JetStream adds persistence, streaming and replay when you need them.

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.

NATS: NATS or Kafka?

NATS is far lighter and lower latency, and much simpler to run. Kafka is the answer when you need a durable replayable log and a large connector ecosystem.

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.

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.

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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