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Continously ingest and deliver both streaming and batch change data from 100s of sources using Estuary's custom no-code connectors.
- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT
Google Cloud SQL for SQL Server connector details
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.
HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.
DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.
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 100s 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.
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Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Speed | <100ms | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale |
Deliver real-time and batch data from DBs, SaaS, APIs, and more
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