Sync Plaid to Google BigQuery

FAQ: Plaid

Is it safe to connect my bank account through Plaid?

Plaid is one of the most widely used financial data networks in the US — it's the same infrastructure behind apps like Venmo, Robinhood, and Mint. Your banking credentials go directly to Plaid, never to Flatly. Flatly only ever receives read-only account data (numbers, dates, transaction text) — it has no ability to move money or access your identity.

Will Flatly be able to see my passwords or log into my bank?

No. You authenticate through Plaid's own secure interface, and Plaid alone communicates with your bank. Flatly receives only a limited, scoped data feed from Plaid — not your credentials or any direct bank access.

Can Flatly move money or make transactions on my behalf?

No. Flatly's access is strictly read-only. It cannot initiate transfers, payments, or any account actions whatsoever.

If I connect multiple bank accounts through Plaid, do they all appear in one file?

It depends on the file format you use. For example with Google Sheets, many datasets can be combined as tabs.

Can I choose a date range for transactions, or does it always pull everything?

You have options. Either Alltime or the "Last X Days" option which is date-rangeable, so you're not forced to pull your full account history on every sync.

Is Plaid available for my bank? What if I'm outside the US?

Flatly's Plaid integration covers 10,000+ financial institutions in the US and Canada. Banks outside those two countries are not currently supported through this integration.

What happens to my Plaid connection if I cancel Flatly?

Connections are automatically revoked if you cancel and stop using Flatly.

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.