Source connector

Zendesk Chat connector

Zendesk Chat integration for databases, warehouses and BI tools

Live chat conversations and agent performance. Datrise captures Zendesk Chat entities such as chats, agents, visitors, departments, and response times, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Zendesk Chat API (Incremental Export endpoints) authenticates with OAuth 2.0, incremental runs key on start_time / start_id (record update timestamp), and Zendesk Chat caps calls at 200 requests per minute per endpoint, reported in the `X-RateLimit` response header; exceeding it returns HTTP 429.

Of the 5 objects, 5 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 `zendesk_chat_chats`) with a schema derived from the Zendesk Chat 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 Zendesk Chat pipeline page, and join the waitlist to get the Zendesk Chat connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Zendesk Chat 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
chats	zendesk_chat_chats	Upsert by primary key, incremental on updated-at
agents	zendesk_chat_agents	Upsert by primary key, incremental on updated-at
visitors	zendesk_chat_visitors	Upsert by primary key, incremental on updated-at
departments	zendesk_chat_departments	Upsert by primary key, incremental on updated-at
response times	zendesk_chat_response_times	Upsert by primary key, incremental on updated-at

Zendesk Chat API: setup facts for the connector

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

API	Zendesk Chat API (Incremental Export endpoints)
Authentication	OAuth 2.0 — OAuth access tokens only — either a Zendesk OAuth token or a Zendesk Chat OAuth token — sent as `Authorization: Bearer {access_token}`; API tokens and basic auth are not supported.
Pagination	cursor — Incremental export endpoints return up to `limit` items (default and maximum 1000) with `count`, `end_time`, `end_id` and a `next_page` URL that should be treated as an opaque string.
Rate limit	200 requests per minute per endpoint, reported in the `X-RateLimit` response header; exceeding it returns HTTP 429
Incremental cursor	start_time / start_id (record update timestamp) — Items come back ordered by update timestamp, so an updated chat reappears in a later window and the destination has to upsert rather than append.
Webhooks	Not published
Bulk export	Yes — Chat Incremental Export (chats, agent_timeline, conversions, department_events)
Deletes detectable	Not published

Official API reference

What bites when replicating Zendesk Chat

`start_time` must be more than five minutes in the past or the export request is rejected outright — a connector that polls for 'now' gets an error, not an empty page.
`start_time` is in seconds for chats, conversions and department_events but in microseconds for agent_timeline, so one shared cursor helper across the four endpoints silently queries the wrong window.
Unlike other Zendesk endpoints, incremental export `next_page` is never null — it always returns the URL for the next poll, so a loop that exits on `next_page == null` never terminates.
The Chat API lives on `https://{subdomain}.zendesk.com/api/v2/chat/` and is rate limited per endpoint at 200/minute, so exporting all four incremental streams in parallel consumes four separate budgets but shares one token.

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Zendesk Chat connector FAQ

What Zendesk Chat data does the connector extract?: 5 objects: chats, agents, visitors, departments and response times. Each lands in its own table with types preserved; history-style objects (0) load as append-only streams.
Is the Zendesk Chat 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 Zendesk Chat data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Zendesk Chat → 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 Zendesk Chat pipeline with guided onboarding

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