Source connector

Convex connector

Convex integration for databases, warehouses and BI tools

Reactive backend with a document database. Datrise captures Convex entities such as documents, tables, functions, indexes, mutations and queries, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Convex Data Sync API (Streaming Export) v1 authenticates with API key, OAuth 2.0, incremental runs key on pagination.nextCursor / upToDate flag on the Data Sync API.

Of the 6 objects, 6 sync as upserts keyed on the primary key and 0 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `convex_documents`) with a schema derived from the Convex API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the Convex pipeline page, and join the waitlist to get the Convex connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Convex data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

Object	Landing table	Sync mode
documents	convex_documents	Upsert by primary key, incremental on updated-at
tables	convex_tables	Upsert by primary key, incremental on updated-at
functions	convex_functions	Upsert by primary key, incremental on updated-at
indexes	convex_indexes	Upsert by primary key, incremental on updated-at
mutations	convex_mutations	Upsert by primary key, incremental on updated-at
queries	convex_queries	Upsert by primary key, incremental on updated-at

Convex API: setup facts for the connector

Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.

API	Convex Data Sync API (Streaming Export) v1
Authentication	API key, OAuth 2.0 — Requests carry an `Authorization` header using a deployment Deploy Key (or an OAuth Team/Project Token) with the `deployment:data:view` permission granted at key-creation time.
Pagination	cursor — `POST /api/v1/data/sync` takes an opaque `cursor` in the request body and returns `pagination.nextCursor` to pass back on the next call, continuing until a page reports `upToDate`.
Rate limit	Not published
Incremental cursor	pagination.nextCursor / upToDate flag on the Data Sync API — There is no timestamp- or SCN-style resumable cursor; the API only exposes the opaque `nextCursor` token, so losing it forces starting a new sync from scratch.
Webhooks	No
Bulk export	Yes — Data Sync API (POST /api/v1/data/sync) and `npx convex export` (ZIP backup)
Deletes detectable	Yes — The Data Sync API response includes a `truncates` array listing tables cleared since the last sync, alongside the `values` array of changed documents

Official API reference

What bites when replicating Convex

The Data Sync API (`/api/v1/data/sync`) requires a Convex Pro plan; projects on the free/Starter plan cannot stream data out at all, only take manual `npx convex export` backups.
The deploy key used to call the API must be explicitly created with the `deployment:data:view` permission scope, or every `/data/sync` call is rejected regardless of the key otherwise being valid.
Deleted or cleared tables surface only through the separate `truncates` array in the response, not the `values` array of changed documents, so an integration that only reads `values` silently misses table-level deletes.
Convex's own streaming-export integration is Fivetran-only; the Airbyte connector Convex maintains supports streaming import into Convex but explicitly does not support streaming export from Convex.

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Convex connector FAQ

What Convex data does the connector extract?: 6 objects: documents, tables, functions, indexes, mutations and queries. Each lands in its own table with types preserved; history-style objects (0) load as append-only streams.
Is the Convex integration incremental?: Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load Convex data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Convex → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your Convex pipeline with guided onboarding

Join the waitlist to get priority access for Convex integrations with guided setup, schema-aware mapping, and production-grade incremental sync.