Databases · head to head
Convex vs RabbitMQ
Convex
Databases
Reactive backend combining a document database, TypeScript server functions and live queries, source-available under the Functional Source Licence.
- From
- Free
- Rated
- -
RabbitMQ
Databases
Open-source message broker supporting AMQP and other protocols
- From
- Free
- Rated
- -
The short version
- 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.; RabbitMQ not built for replay: once consumed, a message is gone, which is exactly what Kafka exists to change
- They diverge on capability: Convex covers Reactive queries, RabbitMQ covers Flexible routing.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Convex and RabbitMQ actually diverge.
Identical on both: starting price (Free), free tier (Yes), 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 RabbitMQ
- Flexible routing
- Multiple protocols
- Management UI
- Clustering and mirroring
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 RabbitMQ
- Agent backends that need durable state, scheduled work and transactional writes without assembling a queue, a database and a cachenot RabbitMQ
- Small product teams who need a complete backend, including auth integration, file storage and subscriptions, without hiring infrastructure engineersnot RabbitMQ
- Prototypes that must become production without a rewrite of the data layer, where end-to-end TypeScript types remove a class of integration bugsnot RabbitMQ
RabbitMQ
- Distributing background jobs to a pool of workers with retriesnot Convex
- Decoupling services that need delivery rather than a replayable historynot Convex
- Routing messages by pattern to different consumers from one publishernot 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.
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
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
RabbitMQ
Free- RabbitMQFree
- Full functionality
- Self-hosted
- No usage limits
Which should you pick?
Choose Convex if
- You need reactive queries.
- You want to start without paying.
- You also want typescript server functions.
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.
Questions people ask
- Is Convex or RabbitMQ better?
- Neither clearly leads. Convex starts at Free and RabbitMQ at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Convex or RabbitMQ?
- Convex starts at Free and RabbitMQ at Free.
- Does Convex or RabbitMQ run on more platforms?
- Convex runs on Web. RabbitMQ runs on Linux, macOS, Windows, Docker, Kubernetes.
- Can I use Convex for free?
- Both have a free tier, so you can try either at no cost before committing.
- 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 RabbitMQ is typically brought in for.
- What can Convex do that RabbitMQ cannot?
- Convex covers Reactive queries, TypeScript server functions, ACID transactions, Document database. RabbitMQ covers Flexible routing, Multiple protocols, Management UI, Clustering and mirroring.
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.
RabbitMQ: Is RabbitMQ free?
Yes, open source with no licence fee. Broadcom sells commercial support.
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.
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.
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.
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.
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.
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.
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