Moving your company's digital infrastructure to the cloud can bring you scalability, cost savings, and innovation. And when you go for Amazon Web Services, you choose an undisputed leader in the cloud market. It offers a robust and comprehensive platform for businesses of all sizes. However, at the heart of any successful cloud migration lies one of the most critical components: your database.

Migrating databases is, indeed, daunting. It involves complex dependencies, critical data, and the potential for significant downtime if not handled right. Let's demystify the process and break down everything you need to know about migrating your databases to AWS. We'll cover the types of AWS databases, the strategies for migration, essential tools for the job, and a step-by-step plan.

Why migrate your database to AWS?

Before diving into the how let's quickly recap the why. Moving your databases from on-premises servers to AWS has compelling advantages:

Why move to AWS?

Scalability and elasticity

AWS allows you to scale your database resources up or down on demand. You pay only for what you use and can avoid the massive capital expenditure of purchasing and maintaining physical hardware that might sit idle.

Enhanced performance

With AWS's global infrastructure, you can position your databases closer to your users to reduce latency. Amazon RDS (Relational Database Service), for example, is optimized for performance with features like Provisioned IOPS.

Improved security and compliance

AWS provides a secure-by-design infrastructure and a shared responsibility model. It offers robust tools for encryption, network security, and access control. You can meet stringent compliance requirements like GDPR, HIPAA, and PCI DSS.

Managed services and reduced overhead

Amazon RDS and Aurora automate time-consuming administrative tasks such as hardware provisioning, database setup, patching, and backups. This frees up your team to focus on innovation rather than routine maintenance.

Disaster recovery and high availability

AWS makes it simple and cost-effective to set up multi-region disaster recovery and high-availability architectures, so your applications remain online even in the face of an outage.

Understanding database types for your AWS migration

The first step in any migration is understanding what you're working with. Databases generally fall into two broad categories: relational and non-relational. AWS has tailored services for both.

Relational databases (SQL)

Relational databases, or SQL databases, have been the standard for decades. They store data in a structured format using tables with rows and columns. They enforce strict schemas and use Structured Query Language for data manipulation and querying.

Common on-premises examples: Oracle, Microsoft SQL Server, MySQL, PostgreSQL.

Key AWS services for relational databases:

  • Amazon RDS: A managed service that simplifies the setup, operation, and scaling of relational databases. It supports several popular database engines, including MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server.
  • Amazon Aurora: A MySQL and PostgreSQL-compatible relational database built for the cloud. AWS claims it delivers the performance and availability of commercial-grade databases at one-tenth the cost. It features a self-healing, fault-tolerant storage system that replicates data across multiple availability zones.

Non-relational databases (NoSQL)

Non-relational databases, or NoSQL, work for unstructured and semi-structured data. They offer flexible schemas and scale out horizontally, which is why they are ideal for modern apps, big data, and real-time use cases.

Common On-Premises Examples: MongoDB, Cassandra, Redis, Couchbase.

Key AWS services for non-relational databases:

  • Amazon DynamoDB: A key-value and document database that delivers single-digit millisecond performance at any scale. It's fully managed, serverless, and perfect for mobile, web, gaming, and IoT applications.
  • Amazon DocumentDB (with MongoDB compatibility): A fast, scalable, and highly available managed document database service that supports MongoDB workloads.
  • Amazon ElastiCache: A managed in-memory data store and cache service, compatible with Redis or Memcached, used to accelerate app and database performance.
  • Amazon Neptune: A managed graph database service for building and running apps that work with highly connected datasets, such as social networking, recommendation engines, and fraud detection.

Once you know your target destination, it's time to choose the migration strategy.

The 6 R's of migration strategy

The right strategy depends on your business goals, technical requirements, and budget. The "6 R's" framework gives a clear way to categorize your approach for each app and its associated database.

6 Rs of migration strategy

Rehost ("Lift and Shift")

This is the most straightforward approach. You move your existing database from your on-premises server to an EC2 (Elastic Compute Cloud) instance in AWS without any changes. It's fast and requires minimal effort, but doesn't take full advantage of cloud-native features.

Replatform ("Lift and Reshape")

This approach involves making a few cloud optimizations without changing the core architecture. A classic example is migrating an on-premises Oracle database to Amazon RDS for Oracle. You offload the database management to AWS and keep the same database engine.

Repurchase ("Drop and Shop")

This means moving to a different product, typically a SaaS solution. For instance, you might move from a self-hosted CRM to Salesforce. Such a strategy applies more to apps than raw databases, but the underlying data migration is a key part.

Refactor / Re-architect

This one is the most complex but also the most transformative strategy. It involves redesigning your app and database to be cloud-native. For example, you can break down a monolithic app with a SQL Server database into microservices running on containers. There, each service can use the best-fit database, like DynamoDB or Aurora Serverless.

Retire

As you assess your portfolio, you'll likely identify apps and databases that you no longer need. Decommissioning these resources saves money and focuses your migration efforts on what truly matters.

Retain

Some apps may not be ready for migration due to regulatory constraints, high-cost dependencies, or simply because they work perfectly well where they are. In this case, you choose to keep them on-premises for the time being.

Depending on the strategy (or strategies) you pick, your final set of tools might differ.

Essential AWS cloud migration tools

AWS gives you a powerful native toolkit, and specialized third-party solutions can fill critical gaps, especially in complex scenarios.

Native AWS tools

  • AWS Database Migration Service helps you migrate databases to AWS securely and with minimal downtime. It supports both homogeneous migrations (e.g., Oracle to Oracle) and heterogeneous migrations (e.g., Oracle to PostgreSQL). DMS handles the replication of data between the source and target.
  • AWS Schema Conversion Tool automatically converts the source database schema (tables, views, stored procedures, functions) to a format compatible with the target database.
  • AWS Application Migration Service is used for rehosting servers. It simplifies the process of migrating physical, virtual, and cloud-based servers to AWS EC2 instances.

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Powerful third-party tools for complex AWS migrations

Native tools are excellent, but they don't cover every edge case. For large-scale, complex, or highly customized environments, specialized tools save lives.

InsightWays for assessment

Before you can migrate, you need a deep understanding of your current environment. A comprehensive assessment tool like InsightWays will help. It automates the discovery and analysis of your entire database estate.

InsightWays scans your source databases (like Oracle or SQL Server) and provides detailed reports on schema complexity, object dependencies, and feature usage. You need this data for choosing the right migration strategy (the "6 R's") and identifying potential roadblocks early.

It gives you a clear, data-driven path forward, estimating the effort required for conversion and helping you select the optimal AWS target database.

SQLWays for code conversion

For heterogeneous migrations (e.g., Oracle to PostgreSQL or SQL Server to Aurora), the biggest challenge is often not the data itself, but the surrounding code and embedded SQL. The AWS SCT does a good job, but it often leaves a significant portion of the code for manual conversion.

SQLWays excels at closing the gap. It is a powerful and highly customizable database and code migration tool. It can automate the conversion of complex stored procedures, functions, triggers, and even embedded SQL within your application source code (Java, C#, etc.).

By providing a much higher level of automation than native tools, SQLWays reduces the time, cost, and risk associated with refactoring projects, making complex re-architecting strategies feasible.

Here's a comprehensive overview of 20 AWS migration tools, where you'll likely find the best fit for your project.

Your step-by-step AWS database migration plan

We can break the migration journey into four distinct phases.

Phase 1: assessment and discovery

This is the most critical phase. Rushing this step is a recipe for disaster.

  1. Define business goals: What are you trying to achieve? Lower costs? Better performance? Faster innovation? Your goals will dictate your strategy.
  2. Inventory your databases: Create a complete list of all databases, their dependencies, performance metrics, and business owners.
  3. Automated assessment: Use InsightWays to perform a deep dive analysis. It will scan your source databases (e.g., Oracle, SQL Server) and provide a comprehensive report on schema complexity, code objects, and feature usage.
  4. Choose your strategy: Based on the assessment from InsightWays and your business goals, apply one of the "6 R's" to each database. Decide whether you will rehost, replatform, refactor, etc.
  5. Select target services: For each database you're migrating, select the appropriate AWS cloud target (e.g., RDS for PostgreSQL, Aurora, DynamoDB). The insights from your assessment will help you make the right choice based on compatibility and performance needs.

Phase 2: planning and design

With a clear strategy, you can now build your detailed plan.

  1. Design target architecture: Design the network, security, and database configurations in AWS. Set up VPCs (virtual private clouds), security groups, IAM (identity and access management) roles, and monitoring.
  2. Create a migration runbook: Document the exact steps, tools, and timelines for the migration. Include pre-migration checklists, the migration process itself, and post-migration validation steps.
  3. Proof of Concept (PoC): Before migrating a production database, conduct a PoC on a non-critical database. You can test your tools, processes, and assumptions. For a refactoring project, this is where you would use a tool like SQLWays to convert a subset of schemas and code to validate the approach and estimate the full project's effort.

Phase 3: migration and modernization

This is the execution phase where the actual move happens.

  1. Schema and code conversion: For heterogeneous migrations, use the AWS SCT and supplement with SQLWays for complex logic. SQLWays will handle the heavy lifting of converting stored procedures, functions, and embedded SQL.
  2. Data replication: Use AWS DMS to replicate the data from your source database to the target AWS database. DMS can perform a one-time full load and then keep the target in sync with the source using ongoing replication.
  3. Test: Test the migrated database, including functional testing, performance testing, and security testing to ensure everything works as expected.

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Phase 4: validation and cutover

The final step is to switch over your apps to the new cloud database.

  1. Final sync: Let AWS DMS perform a final sync to ensure the target database has all the latest data.
  2. Cutover: Update your application connection strings to point to the new AWS database endpoint. This is the moment of truth. Monitor the app for any issues.
  3. Decommission old systems: Once you are confident that the new database is stable and performing well, you can decommission the old on-premises hardware.
  4. Optimize: The journey isn't over. Monitor your database performance and costs in AWS. Use CloudWatch and AWS Trusted Advisor to find opportunities for optimization.

By taking advantage of InsightWays for assessment and SQLWays for code conversion, you can transform a daunting database migration into a strategic initiative that propels your business forward.