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Databases · head to head

Apache Flink vs Convex

Apache Flink logo

Apache Flink

Databases

Stateful stream processing at scale

From
Free
Rated
-
Full reviewWebsite
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

The short version

  • Each has a real cost: Apache Flink genuinely difficult: event time, watermarks and state backends are a real conceptual load before anything works; 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.
  • They diverge on capability: Apache Flink covers Event-time processing, Convex covers Reactive queries.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Apache Flink and Convex actually diverge.

Attributes where Apache Flink and Convex differ
AttributeApache FlinkConvex
Pricing modelOpen source, no licence fee; managed services billed separatelysubscription
PlatformsLinux, Kubernetes, Docker, Self-hostedWeb

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 Apache Flink

  • Event-time processing
  • Exactly-once state
  • Batch and stream
  • SQL interface

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

What people use each for

The jobs each tool is most often brought in to do.

Apache Flink

  • Real-time aggregations and dashboards computed over an event streamnot Convex
  • Fraud and anomaly detection where patterns span a time windownot Convex
  • Joining two live streams where events arrive out of ordernot Convex

Convex

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

Where each one falls short

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

Apache Flink

  • Genuinely difficult: event time, watermarks and state backends are a real conceptual load before anything works
  • Operationally heavy — job managers, task managers, checkpoint storage and state size are all yours to run and tune
  • State grows with the workload, and large state changes recovery time and cost significantly
  • Overkill where a scheduled batch job would answer the same question

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.

Pricing, plan by plan

Apache Flink

Free
  • Apache FlinkFree
    • Full functionality
    • Self-hosted
    • No usage limits

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

Which should you pick?

Choose Apache Flink if

  • You need event-time processing.
  • You want to start without paying.
  • You work on Linux, Kubernetes, Docker, Self-hosted.
  • You also want exactly-once state.
Apache Flink review

Choose Convex if

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

Questions people ask

Is Apache Flink or Convex better?
Neither clearly leads. Apache Flink starts at Free and Convex at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Flink or Convex?
Apache Flink starts at Free and Convex at Free.
Does Apache Flink or Convex run on more platforms?
Apache Flink runs on Linux, Kubernetes, Docker, Self-hosted. Convex runs on Web.
Can I use Apache Flink for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Flink best used for?
Apache Flink is most often used for real-time aggregations and dashboards computed over an event stream, fraud and anomaly detection where patterns span a time window, joining two live streams where events arrive out of order. Of those, real-time aggregations and dashboards computed over an event stream and fraud and anomaly detection where patterns span a time window are not what Convex is typically brought in for.
What can Apache Flink do that Convex cannot?
Apache Flink covers Event-time processing, Exactly-once state, Batch and stream, SQL interface. Convex covers Reactive queries, TypeScript server functions, ACID transactions, Document database.

Answered from the vendors’ own pages

Apache Flink: Is Apache Flink free?

Yes, open source under the Apache Software Foundation. Managed services such as Amazon Managed Service for Apache Flink are billed separately.

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.

Apache Flink: Flink or Kafka?

They are complementary rather than alternatives. Kafka moves and stores events; Flink computes over them with windowing, joins and durable state.

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.

Apache Flink: What is event-time processing?

Computing based on when an event actually occurred rather than when it arrived. It is what makes results correct when data is late or out of order, and it is the main reason Flink is harder than it looks.

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.

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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