Azure SQL Server to Google Cloud SQL for PostgreSQL in Real-Time ETL & CDC

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FASTEST, MOST RELIABLE CDC AND ETL

Move data from Azure SQL Server to Google Cloud SQL for PostgreSQL in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.

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  • 200+Of connectors

  • 5500+Active users

  • <100msEnd-to-end latency

  • 7+GB/secSingle dataflow

How to integrate Azure SQL Server with Google Cloud SQL for PostgreSQL in 3 simple steps

1

Connect Azure SQL Server as your data source

Set up a source connector for Azure SQL Server in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.

2

Configure Google Cloud SQL for PostgreSQL as your destination connector

Estuary supports intelligent schema handling, with schema inference and evolution tools that help align source and destination structures over time. It supports both batch and streaming data movement, reliably delivering data to Google Cloud SQL for PostgreSQL.

3

Deploy and Monitor Your End-to-End Data Pipeline

Launch your pipeline and monitor it from a single UI. Estuary guarantees exactly-once delivery, handles backfills and replays, and scales with your data — without engineering overhead.

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The Microsoft SQL Server connector captures real-time change data (CDC) from your SQL Server database and streams it into Estuary collections, ensuring continuous synchronization across systems.

  • Continuous CDC ingestion: Streams inserts, updates, and deletes directly from SQL Server’s CDC change tables into Flow collections for real-time data pipelines.
  • Broad platform support: Works seamlessly across self-hosted, Azure SQL Database, Amazon RDS, and Google Cloud SQL instances.
  • Automatic schema and instance handling: Detects new capture instances when DDL changes occur (like added columns) and automatically transitions to updated change tables.
  • Granular permissions and automation: Supports automatic capture instance management and change table cleanup when granted db_owner privileges.
  • Flexible and secure connectivity: Connect via SSH tunneling or IP allowlisting for on-premise and cloud-hosted deployments.
  • Customizable configuration: Includes advanced tuning options for backfill chunk size, table skipping, and metadata tagging.

💡 Tip: For optimal reliability, enable Automatic Capture Instance Management to let Flow handle table-level CDC setup and schema evolution automatically, while ensuring the user has the necessary db_owner privileges.

The Google Cloud SQL for PostgreSQL materialization connector in Estuary delivers data from your pipelines directly into your destination system — continuously and in real time. Using merge-based writes, Estuary efficiently updates only changed records, ensuring your destination stays perfectly in sync without unnecessary reprocessing. Whether for analytics, AI, or operational use cases, Estuary provides a reliable, cost-efficient way to keep Google Cloud SQL for PostgreSQL up to date.

  • Merge-based materializations to sync only what's changed
  • Low-latency delivery from streaming and batch sources
  • Automatic schema alignment so your destination matches your pipeline's evolving data
  • Flexible deployment models, including BYOC and hybrid for enterprise governance
  • Unified streaming + batch outputs in a single tool
  • End-to-end security and compliance for sensitive data workloads

Spend 2-5x less

Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.

$1,000 / month

Estimated monthly cost to move 800 GB from Azure SQL Server to Google Cloud SQL for PostgreSQL is approximately $1,000.

Data moved

Choose how much data you want to move from Azure SQL Server to Google Cloud SQL for PostgreSQL each month.

Choose number of sources and destinations.

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Estuary in action

See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.

What customers are saying


  • For AI systems like ours, freshness of data is everything. Estuary gives us sub-second latency without the complexity of maintaining streaming infrastructure ourselves. That reliability means our teams can focus on advancing AI models instead of pipelines.


  • Estuary enabled us to finally implement our ERP’s new data endpoint with all our inventory transactions, purchasing, and shipping data. We can now unlock data blocked by cost before, and sync times are much faster and are always being improved by the Estuary team.

    Read the Success Story

  • “Estuary has been a pleasure to work with and has significantly modernized our data infrastructure, delivering real-time and scalable processes that will significantly impact company-wide operations. Every data-driven organization should be looking at Estuary today.”

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  • Estuary just works. We’ve never had an incident, and it cut our data movement costs in half.

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  • We didn’t want to be locked into a system where faster syncs meant higher bills. Estuary gives us real-time pipelines without pricing games or the burden of running Kafka ourselves.

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  • We needed something self-serve, fast, and reliable, and Estuary delivered exactly that. It’s a huge unlock for our operations, reporting, and machine learning.

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  • Estuary transformed how we operationalize our data for fraud, security, support, and beyond. Instead of unreliable, expensive backfills, we have real-time visibility into platform activity. The proactive support and hands-on approach make all the difference.

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  • Estuary became our real-time data backbone without the cost or complexity of traditional solutions. We replaced a fragile, high-maintenance pipeline with a managed system that just works and scales.

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  • Estuary has been a game-changer for Headset’s data infrastructure. Compared to our previous solutions, it has dramatically improved reliability while reducing our overall costs significantly.

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  • Estuary is our preferred CDC solution for importing data from application databases into BigQuery for analytics. It offers a transparent pricing structure, timely support responses, and an intuitive CLI tool for bulk configuration tasks. In contrast, other market solutions often have ambiguous pricing and fewer options for precise data replication across environments. This makes choosing to use Estuary an obvious decision.


  • Estuary makes tough data transformation problems a piece of cake with its intuitive user interface and incredible breadth of features.


  • Estuary is the only SaaS tool that we found which can do a simple loop and calculate COGS from an array of objects nested in a property. We love to write transformations in typescript because it's in the same codebase and super easy to maintain and read. It's a true game changer.


  • Getting #MINIMA real-time data replication out to the Postgres database was not fun until we found @EstuaryDev it is the best materialization.


  • Estuary makes working with real-time data more cost effective and just as simple as working with batch data.


  • This tool is 1000x times better than LogStash or Elastic Enterprise Data Ingestion Tool.


  • Estuary allows us to integrate low-latency CDC and connect to SaaS apps across our entire reporting stack and it’s the only solution that we’ve found that lets us do both.


  • We needed a platform to help us optimize marketing campaigns with low-latency. Estuary provided an unparalleled solution to do that at terabyte scale.


  • Estuary is the only system we’ve found that can seamlessly replicate large scale Firestore data for analytics. After months of research and trying everything, we can confidently say that Estuary is the only company that can help us get easy, accurate analytics on our data within Snowflake when replicating from Firestore data.


  • We're a big fan of Estuary's real-time, no code model. It's magic that we're getting real time data without much effort and we don't have to spend time thinking about broken pipelines. We've also experienced fantastic support by Estuary.

Why Estuary is the best choice for data integration

Estuary combines streaming and batch data movement capabilities into a unified modern data pipeline. This approach simplifies building and operating pipelines like Azure SQL Server to Google Cloud SQL for PostgreSQL without custom code or orchestration.

Real-time ETL with Estuary: Seamlessly move data from source to destination for immediate analysis and actionable insights.

Increase productivity 4x

With Estuary companies increase productivity 4x and deliver new projects in days, not months. Spend much less time on troubleshooting, and much more on building new features faster. Estuary decouples sources and destinations so you can add and change systems without impacting others, and share data across analytics, apps, and AI.

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Success stories

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Frequently Asked Questions

    How is pricing calculated for moving data from Azure SQL Server to Google Cloud SQL for PostgreSQL?

    Pricing is based on the volume of data moved and the number of active connectors. Use the pricing estimator above to see an estimated monthly cost for your Azure SQL Server to Google Cloud SQL for PostgreSQL pipeline.

DataOps made simple

Add advanced capabilities like schema inference and evolution with a few clicks. Or automate your data pipeline and integrate into your existing DataOps using Estuary's rich CLI.

Schema evolution options

One platform for all data movement