Curriculum Overview: AWS Database Migration Tools (DMS & SCT)
Identifying database migration tools (for example AWS Database Migration Service [AWS DMS], AWS Schema Conversion Tool [AWS SCT])
Curriculum Overview: AWS Database Migration Tools
This curriculum provides a comprehensive breakdown of the tools and strategies required to move database workloads into the AWS Cloud, specifically focusing on AWS Database Migration Service (DMS) and the AWS Schema Conversion Tool (SCT).
Prerequisites
Before starting this module, students should have a foundational understanding of the following:
- AWS Global Infrastructure: Knowledge of Regions and Availability Zones.
- Core Database Services: Familiarity with the differences between Amazon RDS (Relational) and Amazon DynamoDB (NoSQL).
- Deployment Models: Understanding the difference between self-managed databases on Amazon EC2 versus fully managed services like Amazon Aurora.
- Basic Networking: Understanding of VPCs and connectivity (VPN/Direct Connect) between on-premises environments and AWS.
Module Breakdown
| Module | Topic | Primary Tool | Difficulty |
|---|---|---|---|
| 1 | Introduction to Migration | Concepts | Beginner |
| 2 | Schema Conversion | AWS SCT | Intermediate |
| 3 | Data Migration & Replication | AWS DMS | Intermediate |
| 4 | The Integrated Workflow | SCT + DMS | Advanced |
Module Objectives
After completing this curriculum, learners will be able to:
- Identify the appropriate use cases for AWS DMS and AWS SCT.
- Differentiate between Homogeneous (same engine) and Heterogeneous (different engine) migrations.
- Analyze source databases for migration barriers using SCT reports.
- Explain how to minimize downtime during a migration using DMS replication.
- Evaluate licensing implications (e.g., downgrading expensive licenses to open-source engines).
Visual Anchors
The Migration Workflow
This diagram illustrates the relationship between the local SCT tool and the managed DMS service.
Tool Selection Logic
Success Metrics
To demonstrate mastery of this topic, learners must achieve the following:
- Selection Accuracy: Correctly identify whether a scenario requires SCT, DMS, or both in 100% of practice exam questions.
- Report Interpretation: Successfully identify at least three "migration barriers" from a mock SCT analysis report.
- Downtime Strategy: Explain the mechanism DMS uses to keep the source database operational during the migration process.
Real-World Application
[!NOTE] Why this matters in a career: Database migrations are high-stakes projects. Organizations migrate to the cloud to reduce licensing costs (e.g., moving from Oracle to Amazon Aurora) and to eliminate the operational overhead of managing hardware. A Cloud Practitioner who understands these tools can help a company save millions in licensing and prevent catastrophic data loss during the transition.
Examples Section
Below are specific migration scenarios as defined in the AWS Certified Cloud Practitioner requirements:
1. Homogeneous Migration
- Scenario: Moving an on-premises MySQL database to Amazon RDS for MySQL.
- Tool Used: AWS DMS.
- Key Detail: Since the engines are the same, no schema conversion is needed. DMS handles the data movement.
2. Heterogeneous Migration
- Scenario: Moving an on-premises Oracle database to Amazon Aurora PostgreSQL-Compatible Edition.
- Tools Used: AWS SCT (to convert the Oracle schema to PostgreSQL) followed by AWS DMS (to move the actual records).
- Benefit: SCT can identify code in stored procedures that won't work in PostgreSQL and suggest fixes.
3. NoSQL Migration
- Scenario: Moving a MongoDB workload to Amazon DocumentDB.
- Tool Used: AWS DMS.
- Key Detail: DMS supports more than 20 database and analytics engines, including non-relational targets.
4. Data Warehouse Migration
- Scenario: Migrating large-scale data from an on-premises warehouse to Amazon Redshift.
- Tool Used: AWS DMS.
- Key Detail: DMS can be used to funnel data into S3 or Redshift for high-scale analytics workloads.
[!TIP] Remember: AWS SCT is a standalone application you download to your local machine (Windows/Linux), whereas AWS DMS is a managed service running in the AWS Cloud.