BigQuery · warehouse destination

Load your databases into BigQuery, live.

Describe the sync in plain English, approve it once, and rsync.ai streams every change from SQL Server, Postgres, MySQL, or MongoDB into BigQuery — as typed, query-ready tables.

Real-time CDCYou approve every syncNo per-row pricing

Load into BigQuery free →See how a sync runs

Incremental MERGE loads You approve before anything moves

app.rsync.ai / syncs / bigqueryStreaming

✳ Describe the sync

Keep Postgres public.orders and public.customers loaded into BigQuery, live.

Postgressource · CDC

rsync.aiapprove gate

BigQuerywarehouse

Loading into BigQueryIllustrative sync

You approved this syncschema changes applied and recorded

Sources

Bring every source into one BigQuery dataset.

Point rsync.ai at your databases and apps. It builds and runs the pipeline into BigQuery — you approve it before anything moves.

Databases

Log-based CDC keeps operational databases mirrored in BigQuery continuously, not in nightly batches. Deletes are applied as soft-deletes.

SQL ServerPostgreSQLMySQLMongoDB

SaaS & APIs

Pull business objects from the tools your team runs on, on a schedule you set and approve.

StripeGitHub

Files & storage

Ingest Parquet, JSON, or CSV from object storage into typed BigQuery tables.

Amazon S3GCSAzure Blob

What lands

Tables BigQuery is happy to query.

Datasets & tables

Incremental merge

Soft deletes

Schema evolution

Source types → BigQuery

TIMESTAMP / DATETIME

Documents → JSON

How it works

Four steps. Nothing runs until you approve.

Describe it

Say which source and tables to load into BigQuery in plain English — no connector config.

Review the plan

rsync.ai discovers the schema, proposes BigQuery types, and scans columns for likely personal data before a row moves.

Approve

Nothing runs until you say yes. Later schema changes are applied and recorded; only a dropped table waits for you.

Stream

CDC keeps BigQuery up to date; incremental MERGE loads send only the rows that changed.

After it lands

Then work with the data without leaving rsync.ai

Synced tables become something you can query, schedule and share in the same workspace.

SQL Explorer

Run SQL against your connections, with personal columns masked in previews; writes are gated by role and every write is audited.

SQL Explorer docs→

Models

Turn a query into a table that rebuilds on a schedule or when its inputs refresh, with version history and data checks.

Models docs→

Charts and Dashboards

Draw a model or saved query as a chart, then put charts on one live dashboard.

Charts→ · Dashboards→

Workflows and Ask rsync.ai

Schedule reports and data alerts to Slack or email. Describe one in plain English and Ask rsync.ai drafts it.

Scheduled reports→ · Ask rsync.ai→

Compare

Why teams load BigQuery this way.

What you care about	Scheduled queries	Fivetran	Hand-built ETL	rsync.ai
Set up without an engineer	SQL required	Connector forms	No	Plain English
Real-time, log-based CDC	Batch	Yes	Varies	Yes
You approve before it runs	n/a	No	No	Yes
Cost as volume grows	Slot time	Per MAR	Your time	Per GB, not per row
Run in your own VPC	GCP only	No	Varies	Yes

Straight about status: the BigQuery destination and the SQL Server, MongoDB, Postgres, and MySQL sources are live in production. The Stripe and GitHub sources are in preview. Self-hosting in your own VPC is available now — source-available under the rsync.ai Source-Available License — or run rsync.ai as a managed cloud.

FAQ

Loading BigQuery — common questions

How fresh is the data in BigQuery?

You choose the schedule, from a few times a day down to near real time. rsync.ai reads each source's change log (CDC), so it merges only the rows that changed into BigQuery — and a failed run resumes where it stopped instead of reloading the table.

Are tables typed correctly?

Yes. rsync.ai proposes BigQuery-native types based on the source schema, and shows you the plan in the review step. Nothing is created until you approve it, so there are no silent type conversions.

Do I need to write SQL or configure a connector?

No. Describe the sync in plain English. rsync.ai discovers the source schema, maps it to BigQuery, scans columns for likely personal data, and shows you the plan. Nothing runs until you approve it.

How are you priced?

On data volume (GB moved), not per row or Monthly Active Rows. Each plan includes a monthly GB allowance (10 GB on the free month), and pipelines pause at your cap instead of running up charges.

Who controls what moves?

You do. No pipeline is created or started until you confirm the plan, PII rules apply before data lands, and later schema changes are applied and recorded (only a dropped table waits for a person). Self-hosting entirely in your own VPC is available now for teams that need data to never leave their network.

Get your data into BigQuery.

Connect a source free and land your first live tables in BigQuery today — typed and query-ready.

Load into BigQuery free →See how it works

Live on rsync.ai Cloud today · self-hosted (rsync.ai Source-Available License)