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Databases · head to head

RabbitMQ vs turbopuffer

RabbitMQ logo

RabbitMQ

Databases

Open-source message broker supporting AMQP and other protocols

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 RabbitMQ has a free tier, so it costs nothing to try first.
  • Each has a real cost: RabbitMQ not built for replay: once consumed, a message is gone, which is exactly what Kafka exists to change; 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: RabbitMQ covers Flexible routing, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which RabbitMQ and turbopuffer actually diverge.

Attributes where RabbitMQ and turbopuffer differ
AttributeRabbitMQturbopuffer
Starting priceFree$16/month
Pricing modelOpen source, no licence fee; managed services billed separatelysubscription
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 RabbitMQ

  • Flexible routing
  • Multiple protocols
  • Management UI
  • Clustering and mirroring

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.

RabbitMQ

  • Distributing background jobs to a pool of workers with retriesnot turbopuffer
  • Decoupling services that need delivery rather than a replayable historynot turbopuffer
  • Routing messages by pattern to different consumers from one publishernot turbopuffer

turbopuffer

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

Where each one falls short

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

RabbitMQ

  • Not built for replay: once consumed, a message is gone, which is exactly what Kafka exists to change
  • Throughput ceilings are lower than a log-based platform under very heavy streaming loads
  • Queues that build up degrade broker performance, so consumer lag is an operational problem rather than just a backlog
  • Clustering and partition behaviour has historically been a source of hard-to-diagnose problems

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

RabbitMQ

Free
  • RabbitMQFree
    • Full functionality
    • Self-hosted
    • No usage limits

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 RabbitMQ if

  • You need flexible routing.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes.
  • You also want multiple protocols.
RabbitMQ review

Choose turbopuffer if

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

Questions people ask

Is RabbitMQ or turbopuffer better?
Neither clearly leads. RabbitMQ 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, RabbitMQ or turbopuffer?
RabbitMQ has a free tier; the other does not. Paid plans start at Free for RabbitMQ and $16/month for turbopuffer.
Does RabbitMQ or turbopuffer run on more platforms?
RabbitMQ runs on Linux, macOS, Windows, Docker, Kubernetes. turbopuffer runs on Web.
Can I use RabbitMQ for free?
Yes. RabbitMQ has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is RabbitMQ best used for?
RabbitMQ is most often used for distributing background jobs to a pool of workers with retries, decoupling services that need delivery rather than a replayable history, routing messages by pattern to different consumers from one publisher. Of those, distributing background jobs to a pool of workers with retries and decoupling services that need delivery rather than a replayable history are not what turbopuffer is typically brought in for.
What can RabbitMQ do that turbopuffer cannot?
RabbitMQ covers Flexible routing, Multiple protocols, Management UI, Clustering and mirroring. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

Answered from the vendors’ own pages

RabbitMQ: Is RabbitMQ free?

Yes, open source with no licence fee. Broadcom sells commercial support.

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.

RabbitMQ: RabbitMQ or Kafka?

RabbitMQ is a message broker: simpler to run and better at flexible routing and work queues. Kafka is a replayable event log built for very high throughput streaming, and much heavier to operate.

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.

RabbitMQ: Can RabbitMQ replay messages?

Not in the way Kafka can. Messages are removed once acknowledged, so rebuilding state from history is not the model.

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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