Methods of Database Migration
Database migration is the process of transferring meta-objects, data, stored procedures, functions, and triggers from one database management system to another while implementing necessary changes to the application. It also involves preparing, selecting, extracting, and transforming data concerning the differences between the source and target database management systems. The database migration process can be difficult and time-consuming because it requires transferring data between two relational database management systems with different structures and data types. There are several reasons for database migration, including cost, customization, and flexibility.
Database Migration Phases
The first phase in planning a database migration involves an assessment of the application to determine the feasibility of moving it from the source DBMS to the target DBMS. This phase requires a comprehensive analysis of technology-related issues, including an evaluation of the compatibility of the client, application server, data access, and database features. It is essential to ensure that the packaged software application is certified for the target DBMS. If not, you need to persuade the vendor to add support for the new database or select another application.
After ensuring compatibility between the source and target databases, certain prerequisites should be met before initiating data migration, including server resources, operating system, and the installation and configuration of data migration software and related drivers. It is important to ensure that the target server resources are sufficient and scalable enough to handle the volume of data being received.
The next step in the migration process is to identify any discrepancies in schema and data formatting between the source and target database management systems. It is essential to address these differences before the data migration to prevent potential errors that can be frustrating and time-consuming. Performance testing is a crucial step in the migration phase because there may be variations in the functionality of some of the source database built-in transactions or features when transitioning to the target platform, which can impact the application.
Approaches to Data Migration
Various approaches and tools are available in the market for data migration, most of them are based on one of the three methods: snapshot, parallel (multi-threaded) snapshot, and change data capture (CDC). The snapshot method involves taking a snapshot of the source database state and applying it to the target database. Data is moved from the source DBMS to the target all at once, and no WRITE operations are permitted on the source database during the snapshot process. The parallel snapshot involves splitting the data into fragments and snapshots are taken simultaneously. With this approach, the snapshot duration and downtime window are significantly reduced yet still persists.
CDC software is used to track and capture changes in real-time from the source database, and then apply those changes to the target database. There are two techniques of change data capture: trigger-based and transaction log.
Snapshot and parallel (multi-threaded) snapshot methods require some database downtime to avoid data loss or duplication. Also, it may cause essential overhead in the DBMS work due to bulk reading the data. On the other hand, CDC approaches either require modification of the source database (trigger-based) or relies on undocumented and changeable format of transaction log.
The database migration process involves transferring meta-objects, data, stored procedures, functions, and triggers from one database management system to another while implementing necessary changes to the application. The migration process can be challenging and time-consuming due to the differences between the source and target database management systems. The process involves several phases, including assessment, schema migration, functional and performance testing, and data migration. It is essential to address any discrepancies in schema and data formatting between the source and target database management systems before the data migration to prevent potential errors that can be frustrating and time-consuming.