Does Google have a native SQL Server to BigQuery connector?

Yes. BigQuery Data Transfer Service has a Microsoft SQL Server connector, in Preview and free to use while it stays in Preview, with limited support. Datastream can also replicate SQL Server changes into BigQuery from change tables or the transaction log, priced per GiB processed.

Can BigQuery query SQL Server directly with federated queries?

Not through Cloud SQL federation. Google's federated query docs cover Cloud SQL for MySQL and PostgreSQL only, so SQL Server data has to be copied into BigQuery.

Are SQL Server syncs to BigQuery incremental?

They can be. Weld runs full syncs by default, and you switch tables to merge incremental syncs, which need a primary key and a cursor such as updated_at, or append syncs, which need only a cursor.

How are deleted rows handled?

Incremental syncs do not capture deletes. Setting a table to a full sync at midnight removes deleted rows from BigQuery once a day.

Does Weld support SQL Server CDC?

Not yet. SQL Server CDC is in development at Weld and listed as coming soon. Today, syncs are incremental on a cursor column or full.

Does it work with Azure SQL Database and Amazon RDS?

Yes. Weld has connectors for Azure SQL Database and SQL Server on RDS. Azure SQL Database runs the same engine and supports the same sync modes, and authenticates with SQL authentication or a Microsoft Entra ID service principal.

SQL Server to BigQuery

Copy your Microsoft SQL Server tables into BigQuery and keep them current with incremental syncs on a cursor column, plus a nightly full sync where rows get deleted. Weld connects directly or through an SSH tunnel, and lets you drop or hash columns before anything lands.

Start for free View setup guide

4.8 on G2

Source

Weld

Warehouse

Checked against Weld and vendor docs on 10 October 2026

Weld · New sync

SourceMicrosoft SQL ServerConnected

Tables to sync

Your own tables, picked when you set up the sync.

Extract
Load
Keep in sync

DestinationGoogle BigQueryReady

mssql dataset

mssql.Synced
mssql.Syncing
mssql.Synced
mssql.Synced

Trusted by data and AI teams

Options

Three ways to get SQL Server data into BigQuery

Google offers a SQL Server transfer, free while it is in Preview, and Datastream for log-based CDC. BigQuery federated queries do not cover SQL Server. The deciding questions are support level, deletes and whether SQL Server is one source among many.

BigQuery Data Transfer Service

Best for: Trying SQL Server data in BigQuery at no transfer cost
Effort: Low to medium: a transfer config, plus a network attachment if the database has no public IP
Freshness: Hourly, daily or custom schedules, or on demand
Good to know: In Preview, so offered as is with limited support, and free while in Preview. Incremental transfers need a TIMESTAMP watermark column and cannot sync deletes.

Datastream

Best for: Log-based CDC from SQL Server into BigQuery
Effort: Medium: change tables or transaction log setup, plus a stream
Freshness: Continuous, merged into BigQuery on a staleness setting you choose
Good to know: Reads change tables or the transaction log. Express and Web editions are not supported, and Azure SQL Database needs tier S3 or above. Priced per GiB processed.

Weld

Best for: SQL Server alongside your other sources in one pipeline
Effort: Low: connect, pick tables, choose a sync mode per table
Freshness: Incremental and full syncs on your schedule
Good to know: Merge syncs need a primary key and a cursor such as updated_at; append syncs need only a cursor. A full sync at midnight removes deleted rows. Columns can be removed or hashed.

How it works

How to sync Microsoft SQL Server to Google BigQuery with Weld.
In the app, with the API or an agent.

Setup guide API guide MCP docs

Weld · Data warehouse

Data warehouseGoogle BigQueryConnected

Data locationChosen when you connect

CredentialsService account or key, stored encrypted

Data

What lands in Google BigQuery
From Microsoft SQL Server to Google BigQuery.

Weld does not impose a schema on a database source: what lands in BigQuery is the tables you select, with the columns you keep.

Your selected tables
One BigQuery table per SQL Server table you pick, under the destination name you set. Removed columns are left out and hashed columns arrive hashed.
_weld_synced
A timestamp Weld adds to every row with the time it was last synced. Use it to check freshness without touching your own columns.

Example query

How fresh is each replicated table?
In Google BigQuery SQL.

Runs in BigQuery against a dataset named mssql. Replace orders and customers with your own tables; _weld_synced is the column Weld adds to every row.

Google BigQuery · query

1select2  'orders' as table_name,3  count(*) as row_count,4  max(_weld_synced) as last_synced_at,5  timestamp_diff(current_timestamp(), max(_weld_synced), minute) as minutes_since_sync6from mssql.orders7union all8select9  'customers',10  count(*),11  max(_weld_synced),12  timestamp_diff(current_timestamp(), max(_weld_synced), minute)13from mssql.customers14order by minutes_since_sync desc

Weld MCP server

Ask your agent.
It queries Google BigQuery for you.

Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Microsoft SQL Server context, finds the tables it needs and runs the query in Google BigQuery.

Set up the MCP server

Claude CodeOpus 5

ConnectedWeld MCP

Which Microsoft SQL Server tables do we have in Google BigQuery, and which is the largest?

Looking up what Weld has synced from Microsoft SQL Server.

●weld·search_available_references

⎿raw.mssql.*

tables, columns and freshness

●weld·get_reference_schema

⎿columns, types and nullability

●weld·run_query

⎿select count(*) from {{raw.mssql.…}}

submitted

●weld·get_query_status

⎿DONE

●weld·get_query_result

⎿rows returned

✓Answered from Microsoft SQL Server data in Google BigQuery

>Ask about your Microsoft SQL Server dataMCP

Under the hood

Things to know.
Before you sync Microsoft SQL Server.

Tables start on full syncs: Weld's SQL Server connector runs full syncs by default. Switch large tables to incremental to cut sync time and load on the server: merge needs a primary key and a cursor timestamp, ideally updated_at.
Append mode skips updates: Append syncs suit tables without an updated_at column, but they only add new rows at the end of the table, so changes to existing rows are not picked up.
Incremental syncs do not see deletes: Neither merge nor append captures deleted rows. Set tables with frequent deletes to a full sync at midnight, which removes them from BigQuery.
CDC for SQL Server is not live yet: Weld's SQL Server CDC is listed as coming soon. Until then, syncs are scheduled incremental or full syncs, so plan freshness and delete handling around that.

Sources: Weld SQL Server connector docs · Weld SQL Server CDC docs · Weld Azure SQL Database docs · Weld BigQuery setup guide · Weld managed fields · Google Cloud: Load Microsoft SQL Server data into BigQuery · Google Cloud: Datastream SQL Server source · Google Cloud: Datastream pricing · Google Cloud: Cloud SQL federated queries