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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 partitioned, typed, query-ready tables.

Real-time CDCYou approve every syncNo per-row pricing
Load into BigQuery free →See how a sync runs
Partitioned, incremental loads You approve before anything moves
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 within seconds, not nightly batches.

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, byte-checked on every file.

Amazon S3GCSAzure Blob
What lands

Tables BigQuery is happy to query.

Datasets & tables
Partitioned tables
Clustered tables
Incremental merge
Schema evolution
Source types → BigQuery
TIMESTAMP / DATETIME
Nested → STRUCT / JSON
How it works

Four steps. You are in the loop for each one.

01

Describe it

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

02

Review the plan

rsync.ai discovers the schema, proposes partitioning and BigQuery types, and flags any PII before a row moves.

03

Approve

Nothing runs until you say yes. Later source schema changes pause for the same review.

04

Stream

CDC keeps BigQuery live within seconds; incremental merges mean you pay to move only what changed.

Compare

Why teams load BigQuery this way.

What you care aboutScheduled queriesFivetranHand-built ETLrsync.ai
Set up without an engineerSQL requiredConnector formsNoPlain English
Real-time, log-based CDCBatchYesVariesYes
You approve before it runsn/aNoNoYes
Cost as volume growsSlot timePer MARYour timePer GB, not per row
Run in your own VPCGCP onlyNoVariesComing soon

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 coming soon — today rsync.ai runs 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 partitioned and typed correctly?
Yes. rsync.ai proposes BigQuery-native types, partitioning, and clustering 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, flags PII, 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 — so your bill tracks bytes moved, not row counts. Each plan includes a GB allowance, and pipelines pause at the limit rather than silently running up charges; beyond the allowance it's a flat $3/GB.
Who controls what moves?
You do. Every sync waits for your approval, PII is flagged before it lands, and later schema changes pause for review. Self-hosting entirely in your own VPC is coming soon 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 — partitioned, typed, and query-ready.

Load into BigQuery free →See how it works
Live on rsync.ai Cloud today · self-hosting coming soon