Step-by-Step: Using DRPU Database Converter to Convert MySQL to MS SQLMigrating a database from MySQL to Microsoft SQL Server (MS SQL) can be a delicate task: differences in data types, SQL dialects, indexing, and stored procedures all need careful handling. DRPU Database Converter is a commercial tool designed to simplify and automate much of this work. This article walks through a comprehensive, practical step-by-step process for using DRPU Database Converter to move a MySQL database to MS SQL, covers pre-migration planning, addresses common pitfalls, and offers post-migration validation tips.
Why migrate from MySQL to MS SQL?
Choosing MS SQL over MySQL can be driven by several factors:
- Enterprise integration with other Microsoft technologies (e.g., .NET, Azure).
- Advanced tooling and management in SQL Server Management Studio (SSMS).
- Security and compliance features at the enterprise level.
- Performance optimizations for specific workloads.
DRPU Database Converter aims to reduce manual effort while preserving schema, data, indexes, and other database objects as much as possible.
Before you begin — planning and preparation
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Inventory and assessment
- Identify the MySQL databases, tables, views, stored procedures, triggers, and functions you need to migrate.
- Determine data volume and special data types (e.g., BLOBs, JSON).
- Note any platform-specific SQL features or vendor-specific code.
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Environment preparation
- Ensure you have administrative access to the source MySQL server and the target MS SQL server.
- Install the latest DRPU Database Converter version and confirm system requirements.
- Verify network connectivity and that firewalls permit required ports (MySQL default 3306, MS SQL default 1433).
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Backup and rollback plan
- Take full backups of the MySQL database(s).
- Prepare a rollback strategy for the application(s) relying on the database in case migration needs to be reversed.
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Choose migration window
- Pick a low-traffic period for the migration, especially for large databases or production systems.
Step 1 — Install and launch DRPU Database Converter
- Download DRPU Database Converter from the official vendor site and install it on a machine that can access both source and target servers.
- Launch the application. The interface typically presents options to select source and destination database types.
Step 2 — Configure source (MySQL) connection
- Select MySQL as the source database type.
- Enter connection details:
- Hostname/IP
- Port (default 3306)
- Username and password (use a user with SELECT and SHOW VIEW privileges; for schema export you may need additional privileges)
- Database name (or choose multiple databases if supported)
- Test the connection to ensure DRPU can access the MySQL server.
Step 3 — Configure destination (MS SQL) connection
- Select MS SQL (Microsoft SQL Server) as the destination database type.
- Provide connection parameters:
- Server hostname/IP
- Port (default 1433)
- Authentication mode (SQL Server Authentication or Windows Authentication)
- Username and password (with rights to create databases and objects)
- Target database (create a new one or select existing)
- Test the connection.
Step 4 — Select objects to migrate
- In the DRPU interface, choose which objects to convert:
- Tables and data
- Views
- Stored procedures and functions
- Triggers
- Indexes and constraints
- For large databases, consider migrating schema first, then data in batches.
Step 5 — Schema mapping and data type adjustments
- DRPU will automatically map many MySQL types to MS SQL types (for example, MySQL INT → SQL Server INT). Review these mappings carefully.
- Common manual adjustments:
- TEXT and LONGTEXT → nvarchar(max) or varchar(max)
- TINYINT(1) often used for boolean in MySQL → bit in MS SQL (verify application logic)
- DATETIME vs DATETIME2: DATETIME2 has greater precision in SQL Server
- ENUM and SET types: convert to VARCHAR with constraint or lookup table
- Adjust collations/character sets if necessary to preserve text encoding.
Step 6 — Handling keys, indexes, and constraints
- Ensure primary keys and unique constraints are properly converted.
- Verify indexes and their performance characteristics; index names may need renaming to avoid conflicts.
- Foreign keys need careful ordering during data import — DRPU typically disables or defers FK checks while loading data and re-enables them afterward.
Step 7 — Converting stored procedures, functions, and triggers
- MySQL and MS SQL use different procedural languages (MySQL’s procedural extensions vs T-SQL). DRPU may attempt to convert common constructs but manual review and rewriting are often necessary.
- After automatic conversion, open each procedure/function and:
- Fix syntax differences (delimiter handling, variable declaration, loops, handlers).
- Replace MySQL-specific functions (e.g., IFNULL → ISNULL, NOW() → GETDATE()).
- Update error handling and transaction semantics to match T-SQL.
Step 8 — Data migration
- Choose migration mode:
- Full migration in one pass (best during downtime).
- Incremental/batch migration for minimal downtime (migrate static data first, then delta changes).
- For large tables, use batching (e.g., by primary key ranges) to avoid long-running transactions and log growth on SQL Server.
- BLOBs and large objects: verify whether DRPU stores them inline or external; test retrieval after migration.
Step 9 — Validation and testing
- Row counts and checksums
- Compare row counts per table between MySQL and MS SQL.
- Use checksums or hash functions on key columns to validate data integrity.
- Schema validation
- Confirm columns, data types, nullability, default values, constraints, and indexes match expectations.
- Application testing
- Point a test instance of the application at the MS SQL database and run functional tests.
- Test performance-critical queries and stored procedures.
- Fix issues found from tests (type mismatches, logic errors in converted procedures, performance regressions).
Step 10 — Cutover and post-migration tasks
- Final delta sync
- If you used an incremental approach, perform a final sync of changes since the initial migration.
- Switch application connections to the MS SQL server.
- Monitor performance, error logs, and application behavior closely for the first 24–72 hours.
- Rebuild or update statistics and indexes on MS SQL for optimal query plans:
- RUN: ALTER INDEX ALL ON schema.table REBUILD (or use REORGANIZE where appropriate)
- UPDATE STATISTICS as needed.
Common pitfalls and how to avoid them
- Data type mismatches: review and adjust mappings before migrating production data.
- Stored-procedure conversion failures: expect manual rewriting for complex logic.
- Collation and encoding issues: ensure character sets match to avoid corrupted text.
- Referential integrity during import: disable/enforce FKs in correct order and validate afterward.
- Transaction/log growth on SQL Server: use batching and monitor log file size.
Performance tuning after migration
- Update statistics and rebuild indexes.
- Review and add missing indexes based on execution plans observed in MS SQL.
- Consider partitioning very large tables to improve manageability and query performance.
- Use SQL Server’s query store and execution plan comparison tools to identify regressions.
Backup, maintenance, and monitoring
- Set up regular backups (full, differential, and transaction log backups as appropriate).
- Configure maintenance plans: index maintenance, statistics updates, integrity checks.
- Monitor using built-in tools (SQL Server Management Studio, Performance Monitor, Query Store) or third-party monitoring.
Summary checklist
- Backup source data and prepare rollback plan.
- Verify connectivity and permissions for both servers.
- Convert schema with careful data-type mapping.
- Migrate data in appropriate mode (full or incremental).
- Manually review and fix converted stored procedures and triggers.
- Validate data integrity and performance.
- Perform cutover, monitor, and tune the MS SQL environment.
If you want, I can:
- Provide a checklist file you can download and use during migration.
- Show example mappings for specific MySQL data types to MS SQL equivalents.
- Help rewrite a sample MySQL stored procedure into T-SQL.