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Databases · head to head

Convex vs OpenSearch

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
OpenSearch logo

OpenSearch

Databases

Open-source search and analytics suite forked from Elasticsearch

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.; OpenSearch diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • They diverge on capability: Convex covers Reactive queries, OpenSearch covers Full-text search.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Convex and OpenSearch actually diverge.

Attributes where Convex and OpenSearch differ
AttributeConvexOpenSearch
Pricing modelsubscriptionOpen source, no licence fee; managed services billed separately
PlatformsWebLinux, Docker, Kubernetes, Self-hosted

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 OpenSearch

  • Full-text search
  • OpenSearch Dashboards
  • Log analytics
  • Vector search

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

OpenSearch

  • Log and observability storage where an Apache-2.0 licence is a requirementnot Convex
  • Replacing Elasticsearch after the licence change without changing architecturenot Convex
  • Search plus analytics on one cluster rather than two systemsnot 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.

OpenSearch

  • Diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • Operationally heavy in the way Elasticsearch is: cluster sizing, shard strategy and JVM tuning are ongoing work
  • Smaller ecosystem of third-party tooling than Elasticsearch, which most integrations still target first
  • Overkill for plain application search, where a dedicated search engine is far simpler

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

OpenSearch

Free
  • OpenSearchFree
    • 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.
Convex review

Choose OpenSearch if

  • You need full-text search.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want opensearch dashboards.
OpenSearch review

Questions people ask

Is Convex or OpenSearch better?
Neither clearly leads. Convex starts at Free and OpenSearch at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Convex or OpenSearch?
Convex starts at Free and OpenSearch at Free.
Does Convex or OpenSearch run on more platforms?
Convex runs on Web. OpenSearch 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 OpenSearch is typically brought in for.
What can Convex do that OpenSearch cannot?
Convex covers Reactive queries, TypeScript server functions, ACID transactions, Document database. OpenSearch covers Full-text search, OpenSearch Dashboards, Log analytics, Vector 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.

OpenSearch: Is OpenSearch free?

Yes, Apache 2.0 licensed under the Linux Foundation. Amazon OpenSearch Service is a paid managed option.

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.

OpenSearch: Why does OpenSearch exist?

Elastic moved Elasticsearch off the Apache 2.0 licence in 2021. AWS forked the last Apache-licensed version, and the project now sits under the Linux Foundation.

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.

OpenSearch: Is OpenSearch compatible with Elasticsearch?

It was at the 7.10 fork point. Both have developed independently since, so compatibility weakens with every release and should be verified for the features you use.

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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