Sync Firebase Realtime DB to Google BigQuery

Point each sync at any database path

Each sync reads the Realtime Database path you name, so one connection to your project can feed as many syncs as you need, each with its own schedule and destination.

FAQ: Google BigQuery

How does schema setup work?

Flatly leverages intelligent schema generation that adapts to BigQuery's auto-detection protocols, handling data type inference and column ordering automatically so you never have to manually map fields.‍

What about data sanitization?

Data hygiene is built directly into the ingestion process. Before a single row is written to BigQuery, Flatly validates your data against a generated reference schema. It proactively detects and strips out "schema violators" —inconsistent data types or malformed records that would typically cause a load job to crash. Flatly logs these exclusions in a detailed metadata file, ensuring your pipeline remains resilient and continuous while giving you full transparency into data quality issues.‍

How performant and scalable is this integration?

This integration is designed for scale and flexibility, the engine processes data in memory-optimized chunks to handle massive datasets efficiently. It offers powerful pre-load controls, allowing you to filter rows based on custom logic (e.g., date ranges, specific values) and allowlist specific keys. This ensures that you only sync high-value data, optimizing your BigQuery storage costs and query performance.

How does authorization work?

Everything is secured via Service Account authentication, providing a stable, production-grade connection for your most critical analytics dashboards.

What is special about this integration?

Price-to-performance is impressive. Data can be synced to BigQuery every 6 hours for just $19 a month.