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Databases · head to head

Convex vs RisingWave

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
RisingWave logo

RisingWave

Databases

Streaming database that maintains incremental materialised views in SQL instead of Flink jobs

From
Free
Rated
-
Full reviewWebsite

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.; RisingWave anything that does not fit SQL, such as custom windowing, complex event processing or heavy stateful logic, still needs Flink, so RisingWave often adds a system rather than removing one.
  • They diverge on capability: Convex covers Reactive queries, RisingWave covers SQL materialised views.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Convex and RisingWave actually diverge.

Attributes where Convex and RisingWave differ
AttributeConvexRisingWave
Pricing modelsubscriptionPer RisingWave Unit hour
PlatformsWebLinux, Docker, Kubernetes, Cloud

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 RisingWave

  • SQL materialised views
  • Postgres wire compatibility
  • Object storage state
  • Source connectors
  • Sink connectors
  • Iceberg tables
  • Watermarks and windowing
  • User defined functions

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

RisingWave

  • A team with Kafka topics that needs continuously fresh aggregates for a dashboard without standing up a Flink clusternot Convex
  • A fraud or risk team maintaining rolling counters and joins across event streams expressed as SQL viewsnot Convex
  • A company doing Postgres CDC into a real-time denormalised view for search or servingnot Convex
  • An analytics group that wants streaming results landed directly into Apache Iceberg without a separate writer jobnot 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.

RisingWave

  • Anything that does not fit SQL, such as custom windowing, complex event processing or heavy stateful logic, still needs Flink, so RisingWave often adds a system rather than removing one.
  • The Apache 2.0 community edition excludes premium features behind a licence key, and which capabilities sit on which side of that line moves between releases, so a self-hosted plan can be invalidated by an upgrade.
  • Long-running materialised views accumulate state in object storage, and cost and recovery time grow with retention in ways that are hard to forecast before you are in production.
  • The Postgres compatibility is protocol level; it is not a transactional Postgres and using it as a general purpose database, with point updates or high write concurrency, goes badly.
  • It is a comparatively young venture-funded project competing with Flink, Materialize and warehouse-native streaming, and the ecosystem of connectors, operators and third-party expertise is much thinner.

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

RisingWave

Free
  • Community EditionFree
    • Apache 2.0 licence, self-hosted
    • Core streaming engine and connectors
    • Premium features excluded and require a licence key
  • Cloud Basic$0.227/hour
    • Billed per RisingWave Unit hour
    • Hosted on AWS, GCP or Azure
    • Capped at 64 cores
  • Cloud Pro$undefined/year
    • No core limit
    • Bring your own cloud option
    • Premium features included
  • Self-managed Enterprise$undefined/year
    • On premises or Kubernetes
    • Premium features unlocked by licence
    • Annual contract with SLA

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 RisingWave if

  • You need sql materialised views.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Cloud.
  • You also want postgres wire compatibility.
RisingWave review

Questions people ask

Is Convex or RisingWave better?
Neither clearly leads. Convex starts at Free and RisingWave at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Convex or RisingWave?
Convex starts at Free and RisingWave at Free.
Does Convex or RisingWave run on more platforms?
Convex runs on Web. RisingWave runs on Linux, Docker, Kubernetes, Cloud.
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 RisingWave is typically brought in for.
What can Convex do that RisingWave cannot?
Convex covers Reactive queries, TypeScript server functions, ACID transactions, Document database. RisingWave covers SQL materialised views, Postgres wire compatibility, Object storage state, Source connectors.

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.

RisingWave: Is RisingWave open source?

The community edition is Apache 2.0 and self-hostable, but a set of premium features requires a paid licence key.

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.

RisingWave: What does the cloud cost?

It starts at 0.227 US dollars per RisingWave Unit hour on the Basic tier, which is capped at 64 cores.

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.

RisingWave: Does it replace Flink?

For SQL-expressible transformations, often yes. For custom stateful processing and complex event handling, no.

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.

RisingWave: Can I query it like Postgres?

Yes over the Postgres wire protocol, but it is an analytical streaming engine, not a transactional database.

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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