How long does it typically take to migrate from on-premises to AWS using AWS Data Migration Service?

As more organizations seek the scalability, flexibility, and cost-efficiency of cloud computing, migrating on-premises databases to the cloud has become a strategic priority. Amazon Web Services (AWS) offers a robust solution for this need through the AWS Data Migration Service (AWS DMS). This fully managed service enables seamless data migration from on-premises databases to AWS with minimal downtime.

But a common and critical question businesses often ask is: “How long does it take to migrate from on-premises to AWS using AWS DMS?”

The short answer is: It depends. The migration duration can vary from a few hours to several weeks, depending on a range of factors. This article dives into the key variables influencing migration timelines and provides a practical perspective on what to expect.

Overview of AWS DMS

AWS Data Migration Service is designed to help move data between various data stores, including:

On-premises databases to AWS (e.g., SQL Server to Amazon RDS)

Between AWS services (e.g., Amazon RDS to Amazon Redshift)

Between homogeneous and heterogeneous database engines (e.g., Oracle to PostgreSQL)

One of the standout features of AWS DMS is its continuous data replication capability, which ensures minimal downtime and helps support near real-time migrations.

Phases of a Typical AWS DMS Migration

To understand how long a migration will take, it’s important to first break down the migration process into phases:

Assessment and Planning

Schema Conversion and Compatibility Checks

Infrastructure Setup

Full Load Migration

Change Data Capture (CDC) / Ongoing Replication

Testing and Validation

Cutover and Final Sync

Let’s look at each phase in more detail, along with how much time each typically requires.

1. Assessment and Planning (1–2 weeks)

This is arguably the most crucial phase. Here, the existing database environment is assessed for compatibility, dependencies, data volume, and performance requirements. Tools such as AWS Schema Conversion Tool (SCT) and AWS Migration Hub are often used for initial assessment.

Key considerations include:

Source and target database compatibility

Size of the database

Complexity of schema and stored procedures

Network bandwidth and latency

Estimated Time: 1 to 2 weeks, depending on complexity.

2. Schema Conversion and Compatibility Checks (1–10 days)

If you’re migrating between different database engines (e.g., Oracle to Amazon Aurora PostgreSQL), schema conversion is essential. AWS SCT automates much of this, but manual tuning is often required for custom functions or stored procedures.

Estimated Time:

Homogeneous migration: 1–3 days

Heterogeneous migration: 3–10 days

3. Infrastructure Setup (1–3 days)

Setting up the target AWS environment is relatively quick. This includes provisioning:

AWS DMS replication instance

Target databases (e.g., Amazon RDS or EC2-hosted DB)

Networking configurations (e.g., VPC, security groups, VPN or Direct Connect for on-prem)

Automation using Infrastructure as Code (IaC) tools like AWS CloudFormation or Terraform can speed up this phase.

Estimated Time: 1 to 3 days

4. Full Load Migration (Hours to Days)

This is where the bulk of the data is migrated. The duration of this phase largely depends on:

Total size of the data

Network throughput

Type and structure of data (e.g., normalized vs. denormalized tables)

For example:

A 50 GB database over a 100 Mbps link might take several hours.

A 1 TB database may take a couple of days.

AWS DMS supports parallel table loading and data compression to optimize throughput.

Estimated Time: From a few hours to several days.

5. Change Data Capture (CDC) / Ongoing Replication (Hours to Days)

During and after the full load, AWS DMS uses CDC to replicate changes that happen on the source database. This allows businesses to keep their applications online while migrating.

The CDC phase continues until you’re ready to cut over to the new system. The time here depends on:

Volume of transactional data

Desired cutover timing

Acceptable downtime window

Estimated Time: Typically 1 to 3 days, but may be longer for high-transaction environments.

6. Testing and Validation (3–7 days)

Before switching over, it’s critical to:

Test data integrity

Validate application performance

Perform user acceptance testing (UAT)

This step can often reveal schema mismatches or application-layer issues that need resolving before go-live.

Estimated Time: 3 to 7 days

7. Cutover and Final Sync (Few Hours)

Once validation is complete and stakeholders approve, the final cutover involves:

Stopping application writes on the source

Applying any remaining changes via CDC

Redirecting applications to the target AWS database

Estimated Time: Typically a few hours, done during a scheduled maintenance window.

Real-World Migration Timelines

Here are some sample scenarios to illustrate typical timelines:

Migration Scenario Data Size Estimated Total Duration

Small business app (MySQL to RDS MySQL) < 100 GB 3–5 days

Medium eCommerce platform (SQL Server to Aurora) ~500 GB 2–3 weeks

Large enterprise system (Oracle to PostgreSQL) 1–5 TB 4–6 weeks

Factors That Influence Migration Duration

Several key factors influence how long an AWS DMS migration will take:

Database Size: Larger databases naturally take longer to migrate.

Network Bandwidth: Limited bandwidth can severely slow down data transfer.

Source and Target DB Engines: Homogeneous migrations are faster than heterogeneous.

Schema Complexity: The more complex your schema (e.g., stored procedures, triggers), the more time needed for conversion and testing.

Data Change Rate: High transaction volumes require more CDC handling time.

Team Experience: An experienced migration team can streamline the process significantly.

Downtime Tolerance: If zero-downtime is required, additional planning and testing are necessary.

Tips to Speed Up Migration

Use AWS SCT early: Get an early view of schema compatibility issues.

Pre-stage data: Where possible, transfer static historical data in advance.

Optimize DMS settings: Tune memory and parallel thread settings.

Use AWS Snowball: For very large datasets, consider Snowball to physically ship data to AWS.

Automate testing: Automated data validation can reduce manual effort.

Conclusion

There’s no one-size-fits-all answer to how long it takes to migrate from on-premises to AWS using AWS DMS. While some migrations can be completed in a few days, others—especially involving large, complex, or heterogeneous environments—may take several weeks.

The key to a successful and timely migration lies in thorough planning, continuous testing, and leveraging AWS tools effectively. By understanding the phases involved and the variables that influence timelines, businesses can better manage expectations and minimize disruptions during their cloud journey.