1.
What is Database Migration?
This article explains in detail the definition, features, necessity, and methods of performing migration—the process of moving an application, system, or data source from its current location to another, using the most common tools. Continue reading to find comprehensive answers to the question what is migration and others.
Data center migration, data migration is a planning method used by organizations seeking to reshape their IT infrastructure according to changing needs or relocate it to another service provider’s data center. This migration can be physical or virtual. For example, an enterprise migrating its physical servers to a virtual environment also requires migration planning. Naturally, to minimize the risk of data loss or leaks during this process, specialized services are used. These services handle multiple tasks such as data transformation and validation while transferring data from the source to the target. Details on how these tasks are performed can be found in the following sections.
2.
How is Migration Performed?
As briefly mentioned above, the data center migration process involves multiple steps between the source and the target. These steps are critical for both data security and system continuity. Below are the key phases followed during the migration process.
1. Requirements Analysis and Planning
As in any planning process, specific requirements must be identified before performing database migration. First, the organization’s existing IT infrastructure is analyzed, and migration objectives are clarified. Decisions are made about which data, applications, or servers will be migrated. This phase results in the development of the project roadmap.
2. Preparing Source and Target Environments
After conducting the requirements analysis, the next step is to prepare the environments. Necessary resources are created in the target system for the data to be migrated. Components such as hardware, software, and cloud infrastructure are made migration-ready.
3. Data Mapping and Transformation
After preparing the environments, the critical “mapping” and “transformation” stage takes place. Data formats are transformed to ensure compatibility when transferring data from the source system to the target system. This step is essential to minimize potential incompatibilities.
4. Data Transfer
Following the mapping and transformation process, the data is transferred to the target environment using secure protocols. Copying and encryption methods are applied to prevent data loss during this stage.
5. Validation and Testing
Once the transfer is complete, the integrity and accuracy of the migrated data are tested. After confirming that applications and systems function correctly in the new environment, the IT infrastructure becomes ready for production use at the new data provider.
6. Go-Live (Cutover)
After all tests are successfully completed, go-live takes place so that users can begin accessing the new system. The old system is either decommissioned or kept as a backup.
7. Monitoring and Optimization
After the migration is complete, the system is continuously monitored for performance and security, and optimizations are applied as needed.
3.
When is Database Migration Necessary?
When elaborating on what data migration means, it is equally important to understand when database migration becomes necessary. Migration may be required when transitioning to new software or hardware, improving performance and security, or leveraging the convenience offered by modern data storage solutions. Below are the key scenarios explained in detail.
- System Changes: When an organization decides to replace its existing software or hardware with a more advanced technology, database migration becomes inevitable. All data from the old system must be transferred to the new platform without loss to ensure uninterrupted operations.
- Performance Improvements: Over time, databases grow, and system performance may degrade. Data migration is performed to achieve faster processing capacity, improved security infrastructure, or scalable architecture. The goal is to enhance user experience and increase efficiency.
- Data Storage Requirements: As businesses grow, their storage needs increase. When migrating to a server with greater capacity or a cloud-based storage solution, database migration is necessary. This allows cost optimization as well as improved backup and accessibility.
Additionally, it should be noted that while data migration can improve your database, performing it incorrectly can introduce significant risks. Therefore, obtaining professional support and conducting a thorough analysis before implementation are critically important.
4.
Migration Process in Golang
Database Migration Management with Goose
Goose, a migration tool written in the Golang programming language, is designed to manage database schemas using SQL files or Go functions. Supported database drivers include PostgreSQL, MySQL, SQLite3, MSSQL, Redshift, TiDB, ClickHouse, Vertica, and YDB.
Goose Migration Commands
Below are details about the most basic Goose migration commands used during database migration.
- up: Applies the latest migration.
- down: Rolls back the latest migration.
- status: Checks the migration status.
- redo: Rolls back and reapplies the latest migration.
- create: Creates a new migration file.
- reset: Resets the database to its initial state.
- to: Migrates the database to a specific version.
Creating Migration Files with Goose
New migration files can be created using Goose commands. For example, the command goose create add_users_table sql creates an SQL migration file named “add_users_table.” This file can include operations such as creating tables, modifying columns, or updating data. Subsequent file naming and versioning ensure that migration order is maintained.
Applying and Rolling Back
The created migration files are applied to the database using the “goose up” command. If an error occurs or changes need to be reverted, the “goose down” command rolls back the latest migration. This ensures database consistency and allows quick reversal of faulty changes. Additionally, the “goose status” command can be used to track applied and pending migrations.
SQL-Based Migration Process
Details on the SQL-based DB migration process are provided below.
SQL Migration Commands
When performing migrations with SQL, the basic commands used include:
- CREATE TABLE: Creates a new table.
- ALTER TABLE: Modifies existing tables.
- DROP TABLE: Deletes existing tables.
- INSERT INTO: Adds data to a table.
- UPDATE: Updates data in a table.
- DELETE FROM: Deletes data from a table.
Writing Migration Scripts
In SQL, each change is recorded in a separate migration script. These scripts document the changes step by step and serve as references for rollback procedures.
Applying and Rolling Back
Prepared migration scripts are executed to update the database. If an error occurs, rollback commands are used to revert the database to its previous state, minimizing the risk of data loss.
ORM-Based Process with Gorm
Details about database migration with Gorm are provided below.
Gorm Migration Commands
The basic commands used when performing migrations with Gorm include:
- db.AutoMigrate(&Model{}): Applies the model-defined structure to the database.
- db.Migrator().CreateTable(&Model{}): Creates a new table.
- db.Migrator().DropTable(&Model{}): Deletes an existing table.
- db.Migrator().RenameTable(&OldModel{}, &NewModel{}): Renames a table.
Migration Through Models
In Gorm, database tables are typically managed through struct models. Changes made to the models are applied to the database using the db.AutoMigrate command, enabling migration processes without manually writing SQL.
Rollback and Updates
In Gorm, rollback operations can be performed using prepared migration scripts or manual SQL commands. Changes applied via models can be reverted in case of errors, ensuring database integrity.
Essential Steps Before Migration
The following three steps are essential before initiating migration:
- Data Backup: Before migration—meaning copying, moving, or updating all information in the database—performing data backups is critical to minimize risk.
- Testing in a Staging Environment: Test migration commands in a staging environment before moving to production.
- Version Control: Use version control systems for both code and migration files to track changes and enable rollback if necessary. This ensures rapid error detection and minimizes data loss risk.
Additionally, our article on New Trends in Data Center Infrastructure may also interest you.
