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Databases · head to head

Convex vs Teradata

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
Teradata logo

Teradata

Databases

Long-established enterprise MPP data warehouse, rebranded in 2026 as the Autonomous Knowledge Platform, sold for cloud, on-premises and hybrid.

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Convex has a free tier, so it costs nothing to try first.
  • 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.; Teradata licensing is negotiated rather than published, so there is no way to compare total cost against a consumption-priced warehouse without entering a sales cycle, and the comparison is only ever as good as the workload profile you gave them.
  • They diverge on capability: Convex covers Reactive queries, Teradata covers Massively parallel architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Convex and Teradata actually diverge.

Attributes where Convex and Teradata differ
AttributeConvexTeradata
Starting priceFreeOn request
Pricing modelsubscriptionquote
Free tierYesNo

Identical on both: platforms (Web), 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 Teradata

  • Massively parallel architecture
  • Workload management
  • Mature cost-based optimiser
  • Cloud, on-premises and hybrid
  • Bulk load utilities
  • BTEQ scripting
  • In-database analytics
  • Enterprise Vector Store

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

Teradata

  • A large existing Teradata estate where the practical question is which workloads to migrate first rather than whether to adoptnot Convex
  • High-concurrency mixed workloads where hundreds of analysts and scheduled jobs contend and predictable prioritisation matters more than peak single-query speednot Convex
  • Regulated reporting where the same query must produce the same answer for years and the audit trail of the existing implementation has valuenot Convex
  • Hybrid deployments where regulatory or data-residency rules keep a portion of the warehouse on-premises while the rest moves to cloudnot 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.

Teradata

  • Licensing is negotiated rather than published, so there is no way to compare total cost against a consumption-priced warehouse without entering a sales cycle, and the comparison is only ever as good as the workload profile you gave them.
  • The SQL dialect and the loading utilities are Teradata-specific, so every stored procedure, macro and BTEQ script written against the platform is migration debt that grows with each release you ship.
  • Primary index choice determines data distribution, and a poorly chosen index concentrates rows on a few processing units, which surfaces as one slow query rather than an error and needs a specialist to diagnose.
  • The skills market is contracting, so DBA and workload-management expertise is expensive to hire, hard to replace when someone retires, and increasingly hard to buy from consultancies whose own bench has moved to cloud warehouses.
  • The 2026 renaming of Vantage, VantageCloud, ClearScape and QueryGrid split documentation, runbooks and vendor material across two naming systems, so searching for an error or a configuration now returns results for a product that is described under a different name.

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

Teradata

On request

No published plan breakdown. See the Teradata review.

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 Teradata if

  • You need massively parallel architecture.
  • You also want workload management.
Teradata review

Questions people ask

Is Convex or Teradata better?
Neither clearly leads. Convex starts at Free and Teradata at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Convex or Teradata?
Convex has a free tier; the other does not. Paid plans start at Free for Convex and On request for Teradata.
Does Convex or Teradata run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use Convex for free?
Yes. Convex has a free tier, so you can try it without paying. Teradata starts at On request.
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 Teradata is typically brought in for.
What can Convex do that Teradata cannot?
Convex covers Reactive queries, TypeScript server functions, ACID transactions, Document database. Teradata covers Massively parallel architecture, Workload management, Mature cost-based optimiser, Cloud, on-premises and hybrid.

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.

Teradata: Is Teradata only on-premises?

No. It is sold for cloud, on-premises and hybrid deployment, and the cloud offering is now branded Teradata Cloud. A large part of the installed base is still on-premises or hybrid.

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.

Teradata: How does it compare to Snowflake or BigQuery?

On raw elasticity and cost transparency the cloud warehouses win. On mixed-workload concurrency management against a large existing query estate Teradata is still hard to replace, which is why migrations off it take years rather than quarters.

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.

Teradata: Why do organisations stay on it?

Because the cost of leaving is the estate, not the data. Thousands of procedures, scripts and extracts written in a proprietary dialect have to be rewritten and revalidated, and in regulated reporting that revalidation is the expensive part.

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.

Teradata: What changed in the 2026 rebrand?

Vantage became the Autonomous Knowledge Platform, VantageCloud became Teradata Cloud, ClearScape Analytics became AI Studio and QueryGrid became Fabric. The underlying products are continuous with what came before.

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.

Teradata: Can it handle AI and vector workloads?

It has added an Enterprise Vector Store and in-database analytics branded AI Studio. Whether that is preferable to moving the data into a purpose-built vector store depends on how much of your data already lives in the warehouse.

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