AWS Database Migration Service: A Practical Guide

Have you ever tried to modernise a system, only to find the database is the one piece no one wants to touch? Does the word ‘downtime’ send project managers running? Are you facing the need to overhaul your data estate—without tearing everything else apart in the process? Then you’re in the right place.

Migrating databases has always been one of the most fraught steps in cloud adoption. Downtime is expensive, data loss is unforgivable, and the sheer messiness of decades-old schemas can make even experienced teams hesitate. That’s where AWS Database Migration Service (DMS) comes in—a tool purpose-built to streamline the transition and reduce the risks.

This guide offers a practical, vendor-neutral look at how AWS DMS works, when to use it (and when not to), and how to plan a migration that keeps your data safe, your systems running, and your stakeholders happy.

What Is AWS Database Migration Service (DMS)?

Before diving into the how, it helps to understand what AWS DMS actually is. This isn’t just another tool in the AWS arsenal—it’s a specialised service designed to handle one of the most sensitive parts of your cloud journey: moving your data.

According to the AWS User Guide for DMS:

"AWS Database Migration Service (AWS DMS) is a cloud service that makes it possible to migrate relational databases, data warehouses, NoSQL databases, and other types of data stores. You can use AWS DMS to migrate your data into the AWS Cloud or between combinations of cloud and on-premises setups."

In practice, this means AWS DMS allows you to migrate a wide range of data systems without the overhead of manual exports, script-heavy transfers, or prolonged outages. It abstracts the complexities of replication, supports various engine combinations, and enables migrations between cloud and on-premises environments with a strong focus on speed and resilience.

One thing to emphasise is that you don’t need to install agents or set up complex replication frameworks. Instead, you simply provision a replication instance, connect your source and target endpoints, and define a migration task. DMS handles the rest.

Key Features

DMS has a bunch of useful features but it’s the combination of simplicity, flexibility, and low operational overhead that makes it stand out for real-world migrations:

• Supports many database types: Including PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, Amazon RDS, Amazon Redshift, and Amazon S3
• Minimal downtime: Use full load, CDC (Change Data Capture), or both
• Secure and resilient: Built-in monitoring, encryption, and retry mechanisms
• Flexible topologies: Migrate from on-prem to AWS, between cloud regions, or even hybrid environments (with caveats for certain services)

DMS works best for migrating live production systems with minimal disruption—especially when combined with AWS Schema Conversion Tool (SCT) for complex schema translation.

When Should You Use AWS DMS?

Now that we’ve seen what DMS can do, the next question is: should you use it? Not every migration scenario is created equal, and DMS shines brightest under certain conditions.

AWS DMS isn’t always the right tool, but it’s ideal when:

• You need to minimise downtime and keep systems operational during the migration
• You’re migrating to Amazon-native databases like Amazon Aurora or Redshift
• You need to replicate production data to a staging or analytics environment
• You’re planning a hybrid strategy, moving some workloads to the cloud

It’s also commonly used in multi-phase migrations, where data is replicated in parallel while applications are gradually cut over.

That said, DMS is not a backup tool, nor is it a long-term replication solution. It excels in short-term, event-based transitions, not continuous syncing across complex systems. For example, if you're looking to set up ongoing multi-master replication across globally distributed databases, DMS isn’t designed for that. Similarly, if your goal is to archive data for compliance or disaster recovery, you'd be better off using backup and storage-specific services like AWS Backup or Amazon S3 Glacier.

Preparing for a Migration

Once you've decided that DMS fits your needs, preparation becomes the foundation of success. Poor planning leads to missed expectations, avoidable downtime, and frustrating rollbacks. Fortunately, a few key steps can help you move forward with confidence. It’s also worth reviewing these 7 essential migration strategies to align your planning with best practices.

1. Assess Your Environment

• Identify source and target database types
• Audit schema complexity (stored procedures, triggers, non-standard types)
• Check DMS support for your DB engine versions

2. Choose Your Migration Mode

• Homogeneous: Same DB engine on both ends (e.g. SQL Server to RDS SQL Server)
• Heterogeneous: Different engines (e.g. Oracle to PostgreSQL)
• These typically require AWS SCT to convert schema and code objects

3. Plan for Validation

• Set expectations for what DMS doesn’t cover (application rewrites, front-end dependencies)
• Line up data validation tools or scripts

By investing time in discovery and planning, you avoid costly surprises later in the process.

Step-by-Step: Using AWS DMS

With your environment assessed and a plan in place, you're ready to start using DMS. While the service abstracts away much of the heavy lifting, each step plays a critical role in a smooth migration.

Here’s what a typical migration flow looks like:

1. Provision a Replication Instance

• Choose size based on DB volume and replication needs

2. Define Source and Target Endpoints

• Use IAM roles and network configuration (e.g. VPC, security groups)

3. Create and Start Migration Tasks

• Choose migration type: full load, CDC, or both
• Monitor task health and error logs via the AWS DMS Console or CloudWatch

4. Validate Your Data

• Use table comparisons, record counts, or custom checksum queries

5. Cut Over

• When the replicated target DB is in sync, point applications to it

Each phase builds on the last. Testing and validation are not afterthoughts; they’re part of the flow. This step-by-step guide is part of a broader process—see the 7 key steps to a successful cloud migration for a full overview.

Common Pitfalls (and How to Avoid Them)

Even well-prepared migrations can stumble on subtle snags. Here are a few of the most common issues users encounter with DMS, and how to steer clear of them:

• Unsupported Data Types: This is a frequent problem in heterogeneous migrations where the source and target engines use different formats or data structures. Certain data types—like spatial data, custom enums, or binary blobs—may not be supported at all, or may be converted incorrectly. Always consult AWS’s supported engine documentation and run tests early in the process.
• Underpowered Replication Instances: DMS performance is tightly linked to the sizing of the replication instance. Choosing an instance that’s too small can lead to task failures, lagging CDC replication, or excessive latency. Make use of monitoring tools like CloudWatch to keep an eye on CPU, memory, and storage usage, and consider over-provisioning during peak migration windows.
• Permissions Issues: If your IAM roles or database user accounts don’t have sufficient privileges, DMS tasks can fail silently or skip critical operations. Ensure your DMS service role has access to both endpoints, and that your DB users have the required permissions to read from source and write to target. Pay attention to SSL and VPC configurations as well.
• Cross-region limitations: Some AWS-managed services—such as Amazon DynamoDB, Amazon Kinesis, and Amazon OpenSearch Service—do not support DMS tasks that span across regions. If you need to move data between regions, consider staging it in Amazon S3 or using service-specific replication features outside of DMS.

Being aware of these challenges up front allows you to build safeguards into your migration plan.

Cost and Licensing

Whilst we've concentrated mainly on technical details so far, DMS is also more cost-efficient than many realise. With a pay-as-you-go pricing model, there are no hidden licensing fees, and you only pay for the replication instance while it’s running. The model works as follows:

• You pay per-hour for the replication instance
• No license cost for endpoints or volume migrated
• Monitor for idle replication instances post-migration to avoid waste

This makes it especially attractive for short-lived projects. Just remember to shut it off once you're done!

Conclusion: A Lightweight Yet Powerful Tool

Database migration is never trivial—but it doesn't have to be traumatic. With the right tool and a solid plan, it's entirely manageable. AWS DMS offers a streamlined, robust way to transition your data workloads to the cloud or modernised environments with minimal drama.

Plan carefully, validate thoroughly, and consider combining it with tools like AWS SCT for the best results. Whether you’re lifting-and-shifting to RDS, modernising to Aurora, or staging data into S3 for analytics, AWS DMS has you covered.

Further Reading

• AWS Database Migration Service Documentation The official user guide with detailed reference on setup, compatibility, monitoring, and troubleshooting.
• Best Practices for AWS DMS A hands-on AWS blog post offering practical tips to improve performance and avoid common missteps.
• Getting Started with AWS DMS Schema Conversion (YouTube session) A short AWS walkthrough showing how to use Schema Conversion in conjunction with DMS to support heterogeneous migrations.