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Databases · head to head

Convex vs turbopuffer

Convex logo

Convex

Databases

Reactive backend combining a document database, TypeScript server functions and live queries, source-available under the Functional Source Licence.

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 Convex has a free tier, so it costs nothing to try first.
  • Each has a real cost: Convex the Functional Source Licence is not an OSI open source licence: competing use is prohibited until each release reaches its second anniversary and converts to Apache 2.0, so you may self-host but you may not build a service on it.; 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: Convex covers Reactive queries, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Convex and turbopuffer actually diverge.

Attributes where Convex and turbopuffer differ
AttributeConvexturbopuffer
Starting priceFree$16/month
Free tierYesNo

Identical on both: pricing model (subscription), platforms (Web), 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 Convex

  • Reactive queries
  • TypeScript server functions
  • ACID transactions
  • Document database
  • Scheduling and workflows
  • File storage
  • Text and vector search
  • End-to-end types

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.

Convex

  • Collaborative applications where several users see the same data and every client must reflect a change immediatelynot turbopuffer
  • Agent backends that need durable state, scheduled work and transactional writes without assembling a queue, a database and a cachenot turbopuffer
  • Small product teams who need a complete backend, including auth integration, file storage and subscriptions, without hiring infrastructure engineersnot turbopuffer
  • Prototypes that must become production without a rewrite of the data layer, where end-to-end TypeScript types remove a class of integration bugsnot turbopuffer

turbopuffer

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

Where each one falls short

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

Convex

  • The Functional Source Licence is not an OSI open source licence: competing use is prohibited until each release reaches its second anniversary and converts to Apache 2.0, so you may self-host but you may not build a service on it.
  • Transactions are bounded at one second of user code, 16 MiB read and written, 32,000 documents scanned and 16,000 written, so every backfill, migration or bulk import has to be chunked into scheduled batches rather than written as a single operation.
  • There is no SQL and no query planner; you declare up to 32 indexes per table and traverse them, and joins are loops in TypeScript, so an unanticipated access pattern requires a schema and index change rather than a new query.
  • It is not an analytical database, so reporting means streaming data out to a warehouse and BI tools cannot be pointed at Convex directly, which adds a pipeline the architecture diagram did not originally include.
  • The application is written against Convex's function and client APIs rather than a standard protocol, so leaving means rewriting the data access layer and replacing the reactivity model, not repointing a connection string.

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

Convex

Free
  • Free & StarterFree
    • Supports 1-6 developers
    • Reactive database
    • File storage
  • Professional$25/month per developer
    • Supports up to 20 developers
    • All Starter features
    • Log streaming
  • Business & Enterprise$2500/month minimum
    • Supports 50+ developers
    • SAML/SSO
    • Service SLAs

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 Convex if

  • You need reactive queries.
  • You want to start without paying.
  • You also want typescript server functions.
Convex review

Choose turbopuffer if

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

Questions people ask

Is Convex or turbopuffer better?
Neither clearly leads. Convex 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, Convex or turbopuffer?
Convex has a free tier; the other does not. Paid plans start at Free for Convex and $16/month for turbopuffer.
Does Convex or turbopuffer run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use Convex for free?
Yes. Convex has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is Convex best used for?
Convex is most often used for collaborative applications where several users see the same data and every client must reflect a change immediately, agent backends that need durable state, scheduled work and transactional writes without assembling a queue, a database and a cache, small product teams who need a complete backend, including auth integration, file storage and subscriptions, without hiring infrastructure engineers, prototypes that must become production without a rewrite of the data layer, where end-to-end typescript types remove a class of integration bugs. Of those, collaborative applications where several users see the same data and every client must reflect a change immediately and agent backends that need durable state, scheduled work and transactional writes without assembling a queue, a database and a cache are not what turbopuffer is typically brought in for.
What can Convex do that turbopuffer cannot?
Convex covers Reactive queries, TypeScript server functions, ACID transactions, Document database. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

Answered from the vendors’ own pages

Convex: Is Convex open source?

It is source-available under FSL-1.1-Apache-2.0. You may read, modify and self-host it, but competing use is prohibited until each release converts to Apache 2.0 on its second anniversary.

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.

Convex: Can I self-host it?

Yes. The backend, dashboard and CLI can run on your own infrastructure, with most of the features of the cloud product. Self-hosted instances include a telemetry beacon that can be disabled.

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.

Convex: Does it support SQL?

No. Data is accessed through a TypeScript query builder over declared indexes. Relationships are traversed in code, which is explicit and type-safe but means no ad hoc querying.

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.

Convex: What happens if a mutation exceeds the limits?

It fails rather than running longer, so bulk work must be split into batches and scheduled. The limits are per transaction: one second of user code, 16 MiB read and written, 32,000 documents scanned and 16,000 written.

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.

Convex: How does reactivity actually work?

Queries are deterministic functions and Convex records the data each one read. When a mutation changes that data, affected queries are re-run and subscribed clients receive the new result, so cache invalidation is handled by the platform.

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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