Databases · head to head
Convex vs DynamoDB
Convex
Databases
Reactive backend combining a document database, TypeScript server functions and live queries, source-available under the Functional Source Licence.
- From
- Free
- Rated
- -
DynamoDB
Databases
AWS-only managed key-value and document database with fixed per-partition throughput limits and no ad hoc queries.
- 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.; DynamoDB access patterns must be designed into the key schema before launch; a query nobody anticipated needs a new global secondary index, which is a full extra copy of the projected attributes billed as storage and as writes, or an offline migration.
- They diverge on capability: Convex covers Reactive queries, DynamoDB covers Managed and serverless.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Convex and DynamoDB 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 DynamoDB
- Managed and serverless
- Predictable latency
- On-demand or provisioned capacity
- Global secondary indexes
- Transactions
- DynamoDB Streams
- Global tables
- Point-in-time recovery
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 DynamoDB
- Agent backends that need durable state, scheduled work and transactional writes without assembling a queue, a database and a cachenot DynamoDB
- Small product teams who need a complete backend, including auth integration, file storage and subscriptions, without hiring infrastructure engineersnot DynamoDB
- Prototypes that must become production without a rewrite of the data layer, where end-to-end TypeScript types remove a class of integration bugsnot DynamoDB
DynamoDB
- High-volume keyed workloads such as sessions, shopping carts, device state or user profiles where the access pattern is fixed and knownnot Convex
- Traffic that spikes unpredictably, where on-demand capacity absorbs a burst without a capacity-planning exercisenot Convex
- Serverless applications on Lambda, where an HTTP-based datastore avoids the connection pooling problem relational databases havenot Convex
- Event or telemetry ingestion where writes vastly outnumber reads and each record is retrieved by a known identifiernot 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.
DynamoDB
- Access patterns must be designed into the key schema before launch; a query nobody anticipated needs a new global secondary index, which is a full extra copy of the projected attributes billed as storage and as writes, or an offline migration.
- Global secondary indexes are eventually consistent and cannot be read strongly, so a read-after-write against an index can legitimately miss the item that was just written, and application code must be written to tolerate that.
- Per-partition throughput is capped at roughly 3,000 read and 1,000 write units, so a hot key throttles even when the table has spare capacity overall, and the only real fix is changing the key design to spread the load.
- Items are limited to 400 KB and query results paginate at 1 MB, so large or list-shaped data has to be split, offloaded to S3 with a pointer, or read through pagination loops that complicate every consumer.
- It runs only on AWS and the API is proprietary rather than a standard, so moving the data layer means rewriting it; ScyllaDB's Alternator is the only meaningfully compatible target and it brings a much smaller ecosystem.
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$2500/month minimum
- Supports 50+ developers
- SAML/SSO
- Service SLAs
DynamoDB
Free- On-Demand Capacity$null/usage-based
- Pay-per-request pricing with automatic scaling
- Read: 0.5 RRU per 4 KB (eventually consistent), 1 RRU per 4 KB (strongly consistent), 2 RRU per 4 KB (transactional)
- Write: 1 WRU per 1 KB
- Provisioned Capacity$null/hourly
- Fixed hourly charges based on reserved capacity
- RCU rate: $0.00013 per hour (Standard)
- WCU rate: $0.00065 per hour (Standard)
- Standard Table Class Storage$0.25/per GB/month
- $0.25 per GB/month after free tier
- First 25 GB free per month (free tier)
- Standard-Infrequent Access Table Class$0.1/per GB/month
- $0.10 per GB/month
Which should you pick?
Choose Convex if
- You need reactive queries.
- You want to start without paying.
- You also want typescript server functions.
Choose DynamoDB if
- You need managed and serverless.
- You want to start without paying.
- You work on AWS.
- You also want predictable latency.
Questions people ask
- Is Convex or DynamoDB better?
- Neither clearly leads. Convex starts at Free and DynamoDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Convex or DynamoDB?
- Convex starts at Free and DynamoDB at Free.
- Does Convex or DynamoDB run on more platforms?
- Convex runs on Web. DynamoDB runs on AWS.
- 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 DynamoDB is typically brought in for.
- What can Convex do that DynamoDB cannot?
- Convex covers Reactive queries, TypeScript server functions, ACID transactions, Document database. DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes.
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.
DynamoDB: On-demand or provisioned capacity?
On-demand suits unpredictable or spiky traffic and removes capacity planning. Provisioned with autoscaling is considerably cheaper for steady high-volume workloads. Tables can be switched between them, though not arbitrarily often.
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.
DynamoDB: Can I run DynamoDB outside AWS?
No. DynamoDB Local exists for development and testing only. For a production-compatible alternative elsewhere, ScyllaDB's Alternator implements the DynamoDB API, but it is a different system with a different ecosystem.
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.
DynamoDB: Can I run ad hoc queries or analytics?
Not on the table itself. Scans are slow and expensive at scale. The usual pattern is to export to S3 or stream changes out and query them in Athena, Redshift or another analytical engine.
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.
DynamoDB: Is single-table design necessary?
It is the pattern that gets the most from DynamoDB when access patterns are well known, because it lets related items be retrieved in one query. It also makes the model harder to evolve, so many teams reasonably choose multiple simpler tables and accept extra requests.
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.
DynamoDB: What are the real limits I should design around?
400 KB per item, 1 MB per query or scan page, 100 items per transaction, roughly 3,000 read and 1,000 write units per partition, and eventual consistency on global secondary indexes.
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