Source connector

Dataverse connector

Dataverse integration for databases, warehouses and BI tools

Business data platform behind Dynamics and Power Apps. Datrise captures Microsoft Dataverse entities such as tables, rows, columns, relationships, choice sets and change tracking, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Microsoft Dataverse Web API (OData v4) authenticates with OAuth 2.0, incremental runs key on @odata.deltaLink (deltatoken, change tracking), and Dataverse caps calls at 6,000 requests per user per web server within a 5-minute sliding window, plus 1,200 seconds of combined execution time and 52 concurrent requests; exceeding any of the three returns HTTP 429 with a `Retry-After` header.

Of the 6 objects, 5 sync as upserts keyed on the primary key and 1 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 `microsoft_dataverse_tables`) with a schema derived from the Dataverse 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 Dataverse pipeline page, and join the waitlist to get the Dataverse connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Microsoft Dataverse 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
tables	microsoft_dataverse_tables	Upsert by primary key, incremental on updated-at
rows	microsoft_dataverse_rows	Upsert by primary key, incremental on updated-at
columns	microsoft_dataverse_columns	Upsert by primary key, incremental on updated-at
relationships	microsoft_dataverse_relationships	Upsert by primary key, incremental on updated-at
choice sets	microsoft_dataverse_choice_sets	Upsert by primary key, incremental on updated-at
change tracking	microsoft_dataverse_change_tracking	Append-only, incremental by timestamp

Microsoft Dataverse API: setup facts for the connector

Verified against the vendor documentation on 2026-09-03. Unknown values are left blank rather than guessed.

API	Microsoft Dataverse Web API (OData v4)
Authentication	OAuth 2.0 — Microsoft Entra ID OAuth 2.0; server-to-server integrations authenticate as an application user (service principal) mapped to a Dataverse security role.
Pagination	cursor — `@odata.nextLink` in the response body drives paging, and the page size is requested with the `Prefer: odata.maxpagesize` header.
Rate limit	6,000 requests per user per web server within a 5-minute sliding window, plus 1,200 seconds of combined execution time and 52 concurrent requests; exceeding any of the three returns HTTP 429 with a `Retry-After` header
Incremental cursor	@odata.deltaLink (deltatoken, change tracking) — Change tracking is enabled per table; the first request with `Prefer: odata.track-changes` returns every row plus an `@odata.deltaLink`, and later calls against that link return only what changed.
Webhooks	Not published
Bulk export	Yes — Azure Synapse Link for Dataverse (continuous export to a data lake)
Deletes detectable	Yes — The change-tracking delta response includes deleted-record entries, so deletes arrive on the same delta link as updates.

Official API reference

What bites when replicating Microsoft Dataverse

`$filter`, `$orderby`, `$expand` and `$top` are all unsupported alongside the `Prefer: odata.track-changes` header, so a delta query cannot be narrowed server-side and has to be filtered after the fact.
The 6,000-request limit applies per web server and most environments have several, while a trial environment has exactly one — so throughput measured on a trial badly understates production.
Batching with `ExecuteMultiple` sidesteps the request-count limit but burns the 1,200-second combined execution-time budget faster, which is the limit large batches actually trip.
Change tracking has to be turned on per table in Dataverse before any delta query works, so adding a table to a sync is a platform configuration change, not just connector config.

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Microsoft Dataverse connector FAQ

What Dataverse data does the connector extract?: 6 objects: tables, rows, columns, relationships, choice sets and change tracking. Each lands in its own table with types preserved; history-style objects (1: change tracking) load as append-only streams.
Is the Dataverse 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 Dataverse data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Dataverse → 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 Microsoft Dataverse pipeline with guided onboarding

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