Continuous Database Replication: Azure SQL to Amazon RDS Guide

In today’s rapidly evolving IT landscape, the ability to replicate data across cloud platforms is no longer a "nice-to-have" but a necessity. Whether it's for disaster recovery, performance optimization, or a move towards a multicloud strategy, these solutions ensure businesses remain agile, connected, and robust against failovers or downtime. In this guide, let’s unravel the steps to configure continuous database replication from Azure SQL to Amazon Relational Database Service (Amazon RDS) for SQL Server, leveraging SQL Data Sync for Azure.

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Multicloud Database Synchronization: Why it Matters​

Before diving into the technical specifics, let’s address why someone would want to set up this complex replication rig. Enterprises are migrating workloads (often database-heavy) to multicloud environments to:

• Enable Disaster Recovery: Protect workloads against failures in a single cloud through near real-time synchronization.
• Enhance Performance Globally: Host crucial parts of an application closer to regional end-users using different cloud platforms.
• Platform Transition: Migrate databases without halting operations with downtime-free approaches.

For mission-critical applications, replicating data across Azure and AWS allows flexibility, resilience, and adherence to stringent Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO).
That said, Microsoft’s Azure SQL is known for its managed, scalable platform offering, while Amazon RDS for SQL Server is AWS's take on fully managed relational database services for SQL Server workloads. Pairing these heroes together via SQL Data Sync takes cross-cloud symmetry to a new level!

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Key Technologies Involved​

Let’s break down the critical technologies at the heart of this integration:

• Azure SQL: This is Microsoft's Platform as a Service (PaaS) offering, optimized for SQL Server databases. It offers automatic updates, scaling, and built-in threat intelligence, making it an ideal candidate for being a "hub database" in SQL Data Sync’s architecture.
• SQL Data Sync for Azure: A hub-and-spoke-based synchronization tool that connects Azure SQL (as the hub database) with member databases (such as Amazon RDS SQL Server). This tool supports near real-time replication and bi-directional configurations.
• Hub-and-Spoke explained: Imagine the hub database as the sun, radiating synchronization tasks to its satellite members like light beams. This method ensures every spoke (or replication target) mirrors the source.
• Amazon RDS for SQL Server: AWS’s managed relational database service takes SQL workloads natively and simplifies administration, presenting itself as the target for continuous replication here.
• Amazon EC2: Since SQL Data Sync cannot directly interact with Amazon RDS SQL Server, an EC2 instance serves as the bridge hosting the SQL Data Sync Agent.

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The Step-by-Step Transformation​

For those champing at the bit to make this architecture your reality, here’s the exhaustive walkthrough, tailored for Windows professionals. Think of these steps as connective tissue tying Windows Server systems, Azure SQL, and Amazon RDS together:

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Step 1: Prerequisites​

To halt confusion and fragility later, seamlessly meet these requirements first:

On AWS:​

• Amazon RDS Instance: A running SQL Server RDS instance (or optionally, a SQL Server hosted on EC2).
• Amazon EC2 Instance: A Windows Server 2022 instance acting as the sync agent host.

On Azure:​

• Azure Subscription: An account equipped with an Azure SQL database (your source), and optionally, a metadata database for SQL Data Sync logs.

SQL Management:​

• Familiarity: SQL Server Management Studio (SSMS) comes in handy for database scripting.

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Step 2: Deploy the Databases​

• Source Database (Azure SQL): Consider the preferred classic, like the Northwinds sample database, as your replication source.
• Target Database (RDS SQL Server): An empty database (e.g., Northwinds) is created here as your replication destination.

You can deploy databases using the step-by-step wizards in Azure and the Amazon RDS dashboard. Don’t forget to ensure compatibility across schemas, or you risk syncing failures.

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Step 3: Set Up & Configure Azure SQL Data Sync​

• Create a Sync Metadata Database: In Azure, deploy a second SQL database to log metadata changes and syncing relationships. Think of this as the central journal for your sync tasks.
• Set up the Sync Group:
• Locate your hub (source Azure SQL DB) via the Azure portal.
• Use the Sync to other databases option to create a new Sync Group.
• Here, define:
• Sync Direction: Unidirectional: From the Hub. (Bidirectional is optional for multi-source conflict resolution.)
• Automatic Sync Frequency: Define intervals in seconds, minutes, or days to match your RPO.

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Step 4: Deploy the Data Sync Agent​

The magic lies in a small but mighty worker—the Sync Agent—deployed on an Amazon EC2 instance.

• Launch an EC2 instance running Windows Server and ensure it can securely communicate with both AWS RDS and Azure SQL via Private Link.
• Download the SQL Data Sync Agent onto the EC2 instance from Azure's portal, which simplifies communication between the two clouds.
• Register with Azure SQL: During Sync Agent configuration, a Sync Key is required, generated when creating the Sync Agent in the Azure portal.
• Verify Connection: Test EC2-to-Azure connectivity using the agent’s built-in testing tools.

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Step 5: Tie AWS RDS SQL Server to Azure Sync Group​

Head back into Azure’s Data Sync configuration:

• Add an On-Premises Database to the configuration.
• Select your EC2-hosted Sync Agent, specify RDS connection details (SQL Server authentication recommended over Windows Auth for simplicity).

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Step 6: Synchronize and Verify​

Once everything connects:

• Begin the synchronization via the Azure portal.
• Validate synchronization success by running row counts in both the source and target tables. For instance:
  

  sql
  
      SELECT COUNT(*) AS RecordCount FROM Orders;

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Things to Consider​

• Latency Sensitivity: Database sync performance hinges on network latency. Place AWS and Azure resources in proximate regions like the U.S. East hubs.
• Data Egress Charges: Moving data out of Azure SQL attracts costs, so forecast usage.
• Conflict Handling: Bi-directional synchronization must resolve write conflicts with clear rules (e.g., Hub wins vs. Member wins).

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Why Skip DMS and Use SQL Data Sync Here?​

The common question is: Why not use AWS Database Migration Service (DMS)? While DMS is robust, SQL Data Sync reigns supreme in cases like this because:

• Azure SQL-PaaS support is limited in DMS.
• Native support for near real-time synchronization scenarios aligns closer with SQL Data Sync.

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Conclusion​

By using SQL Data Sync for Azure, you can enjoy a multicloud experience with near real-time replication between Azure SQL and Amazon RDS for SQL Server. From seamless migrations and low-downtime platform transitions to ironclad disaster recovery plans, this architecture ticks all boxes for modern database resilience.
Windows and SQL professionals—this is your roadmap to knocking down the walls between Azure and AWS, one sync group at a time!

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Source: Amazon Web Services Continuous Replication to Amazon RDS for SQL Server from Azure SQL