Source connector

Firebase connector

Firebase integration for databases, warehouses and BI tools

App backend with auth, storage, and analytics. Datrise captures Firebase entities such as users, collections, documents, auth events, app events and security rules, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Cloud Firestore API v1 (REST/gRPC) + realtime listeners authenticates with service account, OAuth 2.0, incremental runs key on onSnapshot listener (docChanges).

Of the 6 objects, 4 sync as upserts keyed on the primary key and 2 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 `firebase_users`) with a schema derived from the Firebase 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 Firebase pipeline page, and join the waitlist to get the Firebase connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Firebase 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
users	firebase_users	Upsert by primary key, incremental on updated-at
collections	firebase_collections	Upsert by primary key, incremental on updated-at
documents	firebase_documents	Upsert by primary key, incremental on updated-at
auth events	firebase_auth_events	Append-only, incremental by timestamp
app events	firebase_app_events	Append-only, incremental by timestamp
security rules	firebase_security_rules	Upsert by primary key, incremental on updated-at

Firebase API: setup facts for the connector

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

API	Cloud Firestore API v1 (REST/gRPC) + realtime listeners
Authentication	service account, OAuth 2.0 — Server-side/ETL access uses a service-account OAuth 2.0 token (scope `https://www.googleapis.com/auth/datastore`) that bypasses Firestore Security Rules via IAM instead; client apps instead use Firebase Authentication ID tokens, which are evaluated against Security Rules.
Pagination	cursor — Structured queries (`runQuery`) page with `orderBy` + `startAt`/`startAfter` cursors on a field value or document snapshot; the simpler `ListDocuments` REST endpoint instead uses `pageSize`/`pageToken`.
Rate limit	Not published
Incremental cursor	onSnapshot listener (docChanges) — The only built-in change-capture mechanism is a realtime listener's `docChanges()` (`added`/`modified`/`removed`) on an open connection; there is no server-side `updated_since` filter, so a poll/REST-based connector must maintain its own indexed timestamp field written by the application.
Webhooks	No
Bulk export	Yes — Managed Export/Import (Admin API `ExportDocuments`, LevelDB-format files in Cloud Storage, BigQuery-loadable only when a `collection-ids` filter is set)
Deletes detectable	Yes — A collection query's realtime listener reports `type: "removed"` doc changes while it's attached; there is no REST endpoint to retrieve documents deleted while a connector was disconnected.

Official API reference

What bites when replicating Firebase

There's no server-filterable `updated_since` field: incremental REST/batch sync depends on the application itself writing and indexing a timestamp field, and indexing a field that increases sequentially (like a timestamp) caps that collection's write rate at 500 writes/second, so the very field a connector needs for incremental sync is also Firestore's most common hot-spotting trap.
A realtime listener's first query snapshot reports every existing matching document as an `added` change (not just new ones since the listener attached), so a connector must special-case the first snapshot or it will re-process the entire collection on every reconnect.
New collections are subject to the documented '500/50/5' ramp-up rule (start at 500 ops/second, then increase by only 50% every 5 minutes), so a bulk backfill or high-throughput sync into a brand-new collection that ignores this ramp will get throttled/contended writes rather than a clear rate-limit error.
Deletes are only observable live, through a connected realtime listener's `removed` doc-change events; polling the REST API alone has no way to discover documents deleted while the connector wasn't running, and the managed Export/Import feature exports current state only, with no deleted-document log.

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Firebase connector FAQ

What Firebase data does the connector extract?: 6 objects: users, collections, documents, auth events, app events and security rules. Each lands in its own table with types preserved; history-style objects (2: auth events and app events) load as append-only streams.
Is the Firebase 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 Firebase data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Firebase → 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 Firebase pipeline with guided onboarding

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