Migrating from MySQL to PostgreSQL can unlock better performance, scalability, and advanced SQL features. However, a common concern during this transition is data loss, which can lead to downtime, missing records, and integrity issues. Even minor data mismatches can cause major disruptions, making it essential to follow a structured migration strategy.
A direct transfer between MySQL and PostgreSQL isn’t just about copying tables. These databases have fundamental differences in data types, indexing, and transaction handling. Without proper adjustments, schema mismatches, foreign key failures, and encoding issues can cause serious data inconsistencies. MySQL’s TINYINT doesn’t directly translate to PostgreSQL’s BOOLEAN, and uncommitted transactions can result in missing records. These challenges make it crucial to plan the migration carefully.
This guide covers why data loss happens during migration, the best practices to safeguard information, and how Hevo Data simplifies the process with its integrations and data pipeline.
Now, let’s explore the common causes of data loss and how to prevent them.
Why Data Loss Happens During MySQL to PostgreSQL Migration
Before preventing data loss, it’s important to understand the risks involved in migrating from MySQL to PostgreSQL. These databases differ in structure, transaction handling, and replication methods, making careful planning essential.
- Schema Mismatches
MySQL and PostgreSQL handle data types differently. For example, MySQL’s TINYINT(1) is often used as a boolean, but PostgreSQL requires BOOLEAN. Failing to map these correctly can lead to missing or incorrect values. Similarly, indexing methods and constraints differ, which can affect query performance and data integrity.
- Encoding & Collation Issues
MySQL uses utf8mb4 by default, while PostgreSQL strictly supports UTF-8. If encoding is not correctly adjusted during migration, multi-language data may become corrupted or truncated, causing issues with text-based fields.
- Uncommitted Transactions
If the migration is performed while active transactions are running, some data may be incomplete or lost. This can lead to inconsistencies, especially in systems with high transaction volumes.
- Foreign Key & Constraint Failures
PostgreSQL enforces stricter referential integrity than MySQL. If foreign keys, unique constraints, or primary keys are not correctly mapped, data relationships can break, leading to orphaned records.
- Replication Gaps
If MySQL replication is used for migration, delays or network failures can cause missing transactions. This means certain updates, inserts, or deletions may never reach PostgreSQL, resulting in an incomplete migration.
Understanding these risks is crucial for ensuring a smooth, error-free MySQL to PostgreSQL migration.
Pre-Migration Strategies to Prevent Data Loss
A smooth MySQL to PostgreSQL migration starts with careful planning. Before moving data, it’s essential to implement safeguards to avoid corruption, missing records, or integrity failures. Here’s how you can minimize risks.
- Perform a Full Backup
Before making any changes, take a point-in-time recovery (PITR) backup of your MySQL database. This ensures that if something goes wrong during migration, you can restore data without loss. Use tools like mysqldump or MySQL’s binary logs for a full database snapshot. If working with large datasets, consider incremental backups to reduce downtime.
- Schema Compatibility Check
Since MySQL and PostgreSQL handle data types differently, it’s crucial to verify schema compatibility. Use tools like AWS Schema Conversion Tool or pgloader to map MySQL data types to PostgreSQL-friendly formats. For instance, MySQL’s TEXT may need adjustments in PostgreSQL to avoid performance bottlenecks. Additionally, check for autoincrement primary keys and default values that may require modifications.
- Run a Data Integrity Audit
Before migrating, verify:
- Row counts between MySQL and PostgreSQL to ensure no missing data.
- Indexes and constraints to maintain query performance.
- Foreign key dependencies to prevent broken relationships post-migration.
- Character set compatibility to avoid encoding issues.
- Use a Staging Database
Migrating directly to a production database is risky. Instead, perform a dry run on a staging database to catch schema mismatches, performance slowdowns, and data inconsistencies before switching to live operations.
- Enable Foreign Key Checks
Temporarily disabling foreign keys during migration prevents failures due to missing referenced records. Once the migration is complete, re-enable them and validate relational integrity by checking for orphaned records or constraint violations.
By following these steps, you can prevent data loss and ensure a seamless transition from MySQL to PostgreSQL.
Safe Methods for MySQL to PostgreSQL Migration
Method 1: Logical Dump & Load (For Small Databases)
- Use mysqldump –compatible=postgresql to export data.
- Modify schema inconsistencies manually.
- Import data into PostgreSQL using psql or pg_restore.
Best for small databases with limited foreign key dependencies.
Method 2: PgLoader (For Automated Schema & Data Migration)
- Converts MySQL types to PostgreSQL equivalents automatically.
- Handles bulk data migration efficiently.
- Provides error handling and retry mechanisms.
Ideal for medium-sized databases needing structured schema conversion.
Method 3: Continuous Replication (For Zero Downtime Migration)
- Uses Change Data Capture (CDC) tools like Debezium or Hevo Data.
- Transfers change in real-time from MySQL to PostgreSQL.
- Ensures no data loss or downtime during migration.
Best for large-scale applications that require uninterrupted access to data.
Automating Migration & Preventing Data Loss with Hevo Data
Migrating databases manually comes with high risks, errors, and downtime. This is where Hevo Data simplifies the process.
Hevo Data Integrations: Connect MySQL and PostgreSQL Seamlessly
- One-click integration between MySQL and PostgreSQL.
- Automatic schema mapping to adjust for data type differences.
- Real-time monitoring to detect and fix anomalies instantly.
Hevo Data Pipeline: Secure, Zero-Loss Migration
- Continuous data replication ensures every transaction is migrated.
- Error handling & rollback prevent skipped or failed records.
- Minimal performance impact, allowing normal database operations during migration.
With Hevo Data, businesses can avoid downtime, prevent data loss, and complete the migration seamlessly.
Post-Migration Validation Checklist to Confirm No Data Loss
Once MySQL data is migrated to PostgreSQL, verifying accuracy is crucial to prevent inconsistencies. A structured validation process ensures data integrity and prevents post-migration issues.
1. Compare Row & Record Counts
Check if MySQL and PostgreSQL contain the same number of records. Missing or duplicate entries could indicate migration errors.
2. Verify Foreign Keys & Indexes
Ensure foreign keys correctly link related records and indexes are applied properly. This helps maintain query performance and data relationships.
3. Run Data Consistency Queries
Test queries should confirm the following:
- Primary and foreign key relationships remain intact.
- Indexed searches return accurate results.
- Unique constraints prevent duplicate data.
4. Monitor Logs & Identify Errors
Review migration logs for skipped records, transaction failures, or replication lags. Address anomalies before finalizing the migration.
By conducting these checks, you can confirm data consistency and avoid post-migration failures. A thorough validation ensures PostgreSQL reflects the original MySQL dataset accurately, preventing costly data loss or system downtime.
Conclusion
Data loss during MySQL to PostgreSQL migration is preventable with the right strategy. Schema mismatches, encoding issues, and replication gaps are common pitfalls, but careful pre-migration planning, structured migration methods, and post-migration validation can ensure a successful transition.
Instead of dealing with manual migration risks, businesses can use MySQL to PostgreSQL migration with Hevo Data. Schedule a Free Demo Right Now!
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