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Load Data to Google Cloud SQL for SQL Server in Real-time ETL & CDC

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REAL-TIME ETL & CDC

Stream into Google Cloud SQL for SQL Server with your free account

Continously ingest and deliver both streaming and batch change data from 150+ of sources using Estuary's custom no-code connectors.

  • <100ms Data pipelines
  • 200+ Connectors
  • 2-5x less than batch ELT

01. Select a source02. Transform in-flight03. Deliver to Google Cloud SQL for SQL Server

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Connecting Google Cloud SQL for SQL Server with Estuary lets you automatically sync data from Flow collections into SQL Server tables hosted on Google Cloud. This integration enables teams to materialize real-time data for analytics, reporting, and application backends without maintaining complex pipelines.

  • Fully managed setup: Works with any SQL Server instance hosted on Google Cloud SQL (2017 or later)
  • Automated table creation: Flow generates and updates tables automatically based on your collection schema
  • Flexible connectivity: Supports both direct public IP access and secure SSH tunneling through a Google Cloud VM
  • Easy user setup: Create a dedicated database user (flow_materialize) with control privileges using standard SQL commands
  • Delta update support: Choose between standard merge operations or delta updates for more efficient synchronization
  • Secure configuration: Password-based or SSH key–based authentication ensures safe communication between Flow and your SQL Server environment

💡 Tip: Use SSH tunneling if your instance does not allow public IP access. Set the address to _127.0.0.1:5432_ and provide your VM credentials under the _networkTunnel_ configuration.

How to connect your data source to Google Cloud SQL for SQL Server in 3 easy steps

1

Connect your data source

Select from more than 100 supported databases and SaaS platforms including PostgreSQL, MySQL, SQL Server, MongoDB, and Kafka.

2

Prepare and transform your data

Apply transformations and schema mapping as data moves whether you are streaming in real time or loading in batches.

3

Sync to Google Cloud SQL for SQL Server

Continuously or periodically deliver data into your destination with support for change data capture and reliable delivery for accurate insights.

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HIGH THROUGHPUT

Distributed event-driven architecture enable boundless scaling with exactly-once semantics.

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DURABLE REPLICATION

Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.

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REAL-TIME INGESTION

Capture and relay every insert, update, and delete in milliseconds.

Real-timehigh throughput

Point a connector and replicate changes to Google Cloud SQL for SQL Server in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 200+ of batch and real-time connectors to move and transform data using ELT and ETL.

  • Ensure your Google Cloud SQL for SQL Server insights always reflect the latest data by connecting your databases to Google Cloud SQL for SQL Server with change data capture.
  • Or connect critical SaaS apps to Google Cloud SQL for SQL Server with real-time data pipelines.

See how you can integrate any source with Google Cloud SQL for SQL Server:

Details

or choose from these popular data sources:

Don't see a connector?Request and our team will get back to you in 24 hours

Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.

Feature Comparison

EstuaryBatch ELT/ETLDIY PythonKafka
Price$$$-$$$$$-$$$$$-$$$$
Speed<100ms5min+Varies<100ms
EaseAnalysts can manageAnalysts can manageData EngineerSenior Data Engineer
Scale
Maintenance EffortLowMediumHighHigh

Detailed Comparison

Deliver real-time and batch data from DBs, SaaS, APIs, and more

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