Databases · head to head
Convex vs Redpanda
Convex
Databases
Reactive backend combining a document database, TypeScript server functions and live queries, source-available under the Functional Source Licence.
- From
- Free
- Rated
- -
Redpanda
Databases
Kafka-compatible streaming platform with no ZooKeeper or JVM
- 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.; Redpanda the community edition is source-available rather than OSI open source, which matters for some procurement
- They diverge on capability: Convex covers Reactive queries, Redpanda covers Kafka API compatible.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Convex and Redpanda 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 Redpanda
- Kafka API compatible
- No JVM or ZooKeeper
- Thread-per-core
- Built-in HTTP proxy and schema registry
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 Redpanda
- Agent backends that need durable state, scheduled work and transactional writes without assembling a queue, a database and a cachenot Redpanda
- Small product teams who need a complete backend, including auth integration, file storage and subscriptions, without hiring infrastructure engineersnot Redpanda
- Prototypes that must become production without a rewrite of the data layer, where end-to-end TypeScript types remove a class of integration bugsnot Redpanda
Redpanda
- Kafka workloads where the operational cost of running Kafka is the blockernot Convex
- Latency-sensitive streaming where tail latency mattersnot Convex
- Smaller teams wanting streaming without a dedicated platform groupnot 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.
Redpanda
- The community edition is source-available rather than OSI open source, which matters for some procurement
- Kafka API compatibility is high but not total, and deep ecosystem tools can hit gaps
- Smaller community than Kafka, so fewer people have solved your problem before
- Some operational and tiered-storage features are enterprise-only
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
Redpanda
Free- CommunityFree
- Kafka-compatible broker
- Single binary
- Community support
Which should you pick?
Choose Convex if
- You need reactive queries.
- You want to start without paying.
- You also want typescript server functions.
Choose Redpanda if
- You need kafka api compatible.
- You want to start without paying.
- You work on Linux, Docker, Kubernetes, Self-hosted.
- You also want no jvm or zookeeper.
Questions people ask
- Is Convex or Redpanda better?
- Neither clearly leads. Convex starts at Free and Redpanda at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Convex or Redpanda?
- Convex starts at Free and Redpanda at Free.
- Does Convex or Redpanda run on more platforms?
- Convex runs on Web. Redpanda runs on Linux, Docker, Kubernetes, Self-hosted.
- 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 Redpanda is typically brought in for.
- What can Convex do that Redpanda cannot?
- Convex covers Reactive queries, TypeScript server functions, ACID transactions, Document database. Redpanda covers Kafka API compatible, No JVM or ZooKeeper, Thread-per-core, Built-in HTTP proxy and schema registry.
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.
Redpanda: Is Redpanda free?
A community edition is free and source-available. Enterprise features and Redpanda Cloud are paid, and the licence is not OSI open source.
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.
Redpanda: Can I use my Kafka clients?
Yes. Redpanda implements the Kafka API, so existing clients and most tooling connect without changes.
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.
Redpanda: Why remove ZooKeeper and the JVM?
Both are significant sources of Kafka’s operational burden — tuning, coordination and failure modes. Removing them is the core of Redpanda’s pitch.
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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