Firebase to DuckDB Integration

How Datrise loads Firebase into DuckDB

Datrise syncs Firebase's users, collections, documents, auth events, app events, and security rules into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

Firebase: App backend with auth, storage, and analytics.

DuckDB: In-process analytics database for fast local OLAP.

How Firebase entities map to DuckDB

Firebase entity	DuckDB object	Notes
users	`firebase_users`	id PK · custom fields → JSON or STRUCT columns
collections	`firebase_collections`	id PK · linked to firebase_users
documents	`firebase_documents`	id PK · linked to firebase_users
auth events	`firebase_auth_events`	TIMESTAMP WITH TIME ZONE events

FAQ

How does Datrise handle Firebase's custom fields in DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the Firebase to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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