AWS DMS: Simplify Database Migration
Group COO & CISO
Operational excellence, governance, and information security. Aligns technology, risk, and business outcomes in complex IT environments

What Is AWS Database Migration Service?
AWS Database Migration Service (DMS) migrates databases to AWS with minimal downtime by continuously replicating data from the source database while applications continue to operate. It supports homogeneous migrations (same engine to same engine) and heterogeneous migrations (different engine types) with the AWS Schema Conversion Tool.
In 2026, AWS DMS remains the primary tool for database migration to AWS, supporting relational databases, NoSQL databases, and data warehouses. It has evolved to handle increasingly complex migration scenarios including multi-database consolidated migrations.
How AWS DMS Works
AWS DMS creates a replication instance that connects to source and target databases, performing an initial full load followed by continuous change data capture.
| Phase | What Happens | Duration |
|---|---|---|
| Setup | Create replication instance, source/target endpoints | Minutes |
| Full Load | Copy all existing data to target | Hours to days |
| CDC (Change Data Capture) | Replicate ongoing changes | Continuous until cutover |
| Validation | Verify data consistency | Minutes to hours |
| Cutover | Switch applications to target database | Minutes |
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Supported Database Engines
AWS DMS supports migration from and to a wide range of database engines, enabling both cloud migration and database platform changes.
- Sources: Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, MariaDB, SAP ASE, DB2, and more
- Targets: Amazon RDS (all engines), Aurora, DynamoDB, Redshift, S3, and more
- Heterogeneous migration: Oracle to PostgreSQL, SQL Server to MySQL, and other cross-engine migrations using Schema Conversion Tool
AWS Schema Conversion Tool
The Schema Conversion Tool (SCT) converts database schema, stored procedures, and application SQL from one engine to another, making heterogeneous migration feasible.
- Automatically converts 80-90% of schema objects for common migration paths
- Highlights code that requires manual conversion with complexity ratings
- Generates migration assessment reports with estimated effort
- Supports conversion of SQL embedded in application code
DMS Best Practices
Following these best practices ensures reliable database migration with minimal downtime and data loss risk.
- Size replication instances appropriately for source database volume and change rate
- Use multi-AZ replication instances for production migrations
- Run full-load validation to verify row counts and data integrity
- Test cutover procedure multiple times before production cutover
- Monitor replication latency and CDC throughput during continuous replication
Combine DMS with AWS Application Migration Service for complete application and database migration. Get expert support from AWS consultants.
Common Migration Scenarios
AWS DMS handles various migration scenarios with different complexity levels and tooling requirements.
- Oracle to Aurora PostgreSQL: Most common enterprise migration, use SCT for schema conversion
- SQL Server to RDS SQL Server: Straightforward homogeneous migration
- MongoDB to DynamoDB: NoSQL migration with data model transformation
- On-premises to RDS: Standard cloud migration with DMS handling replication
Explore broader migration strategies in our cloud migration guide and managed services for post-migration support.
Frequently Asked Questions
How much downtime does DMS migration require?
DMS enables near-zero downtime migration. The cutover window is typically minutes to a few hours, mainly for final data synchronization and application endpoint switching. Applications run against the source database until cutover.
How much does AWS DMS cost?
DMS charges for the replication instance (similar to EC2 pricing) and data transfer. A typical migration uses a dms.r5.large instance at approximately $0.30/hour. Total migration costs depend on duration and instance size.
Can DMS handle large databases?
Yes. DMS handles databases of any size. For very large databases (terabytes), optimize by using larger replication instances, enabling parallel full load, and considering AWS Snowball for initial data transfer to reduce replication time.
What is the difference between full load and CDC?
Full load copies all existing data from source to target as a one-time operation. CDC (Change Data Capture) continuously replicates ongoing changes after the full load. Together, they enable migration with minimal downtime.
Do I need the Schema Conversion Tool?
SCT is needed for heterogeneous migrations (different database engines). Homogeneous migrations (same engine) do not need schema conversion. SCT is also useful for assessing migration complexity before committing to an engine change.
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About the Author

Group COO & CISO at Opsio
Operational excellence, governance, and information security. Aligns technology, risk, and business outcomes in complex IT environments
Editorial standards: This article was written by a certified practitioner and peer-reviewed by our engineering team. We update content quarterly to ensure technical accuracy. Opsio maintains editorial independence — we recommend solutions based on technical merit, not commercial relationships.