Summary: Today, many teams are moving from MySQL to PostgreSQL as they update their database systems and plan for future growth. However, too often, there is extra work after the migration: for example checking that tables and constraints were copied correctly, tuning performance, and confirming that replication works properly.
Devart’s PostgreSQL tools help DBAs with these tasks through features like Schema Compare, Data Compare, and other tools that help review and manage PostgreSQL databases.
The challenge
Many organizations look at PostgreSQL when planning the future of their database systems or when they want more flexibility from open-source software. However, moving from MySQL to PostgreSQL means handling several technical tasks during and after the migration:
- Autovacuum tuning: PostgreSQL uses autovacuum to clean up old rows and stop tables from growing too large. If it is not set up properly, it may run too often or not often enough, which can slow down systems.
- Replication setup: The database supports different types of replication, including streaming and logical replication. DBAs need to monitor replication and set it up correctly to make sure data stays the same across all servers.
- Performance optimization: Workloads moved from MySQL may need changes to indexes, queries, and storage settings so they run well in PostgreSQL.
- Operational tooling: Teams migrating from MySQL often look for management tools that help them see database structure, check query performance, and keep environments in sync.
The solution
Devart’s dbForge tools for PostgreSQL help teams check and manage PostgreSQL systems after a migration.
The migration itself is usually done with tools such as pgloader, AWS Database Migration Service, or other tools that move schema and data.
After the process is finished, dbForge Studio for PostgreSQL helps DBAs review database structure, compare databases, and make sure the new PostgreSQL system works properly. Tools like Schema Compare, Data Compare, query profiling, and other database tools help teams check the migration results and keep databases consistent across development, test, and production environments.
These tools also help DBAs better understand how their database is working and allow them to:
- Optimize performance by finding slow queries and reviewing query plans.
- Validate schema and data by comparing databases across homogeneous environments.
- Monitor replication by checking replication status across servers.
- Help developers work faster with a simple workspace for queries and database exploration.
Steps after migrating from MySQL to PostgreSQL
To make sure everything is working correctly, DBAs usually run a few quick checks.
Step 1: Check tables and constraints
Schema and data migration is usually done with tools such as pgloader, AWS Database Migration Service, or other migration tools that move data from MySQL to PostgreSQL.
After the migration is finished, DBAs check that tables and constraints were copied correctly. Constraints like primary keys, foreign keys, and unique constraints are especially important because they keep the data correct.
One common step is to check PostgreSQL’s system catalog to make sure the expected constraints exist on the migrated tables.
SELECT conname, contype
FROM pg_catalog.pg_constraint
WHERE conrelid = 'public.your_table'::regclass; This type of query helps ensure that important integrity rules were preserved during the migration process.
Step 2: Review performance and autovacuum settings
After a migration, DBAs often review how autovacuum works in PostgreSQL. In tables that receive many writes, old rows can build up quickly. If cleanup does not run often enough, tables can grow too large and queries may slow down.
In some cases, DBAs adjust autovacuum settings for specific tables instead of using the same settings for the whole database.
The following example shows how autovacuum settings can be changed for a busy table. These values are only examples and should always be tested and monitored before being used in a production system.
ALTER TABLE high_volume_table SET (
autovacuum_vacuum_scale_factor = 0.01,
autovacuum_analyze_scale_factor = 0.005
); Monitoring query activity and vacuum statistics helps determine whether these adjustments are appropriate for a given workload.
Step 3: Monitor logical replication
When PostgreSQL environments use logical replication, DBAs monitor replication status to ensure that subscriptions remain active and that data changes are applied correctly.
PostgreSQL shows this information through system views like pg_stat_subscription, which help DBAs see the status of logical replication subscriptions.
SELECT subname,
pid,
status,
received_lsn,
latest_end_lsn,
latest_end_time
FROM pg_stat_subscription; Monitoring these metrics helps administrators detect replication delays or synchronization issues before they affect application behavior.
Step 4: Automate regular database tasks
Once the PostgreSQL environment is stable, teams often automate regular tasks such as backups, schema checks, and data checks.
Command-line tools and database management utilities can schedule these operations and integrate them into CI/CD pipelines, ensuring that PostgreSQL environments remain consistent and well-maintained as systems evolve.
Key benefits
The following table shows how using Devart’s PostgreSQL tools helps teams better understand their databases and keep them consistent across different environments.
| Feature | Benefit for DBAs | Business Impact |
|---|---|---|
| Visual Query Profiling | Find slow queries and performance problems | Faster applications |
| Schema & Data Compare | Compare schemas and data across databases | Safer updates and deployments |
| Database Diagnostics | Review database activity and query plans | Faster problem solving |
| CLI Automation | Run comparisons and checks from the command line | Less manual work |
Conclusion
Moving from MySQL to PostgreSQL can be a smooth process when teams have the right tools to check the migration, tune performance, and manage the database.
The migration itself is usually done with tools designed to move data from one database to another. After the move, tools like dbForge Studio for PostgreSQL help DBAs review database structure, compare databases, and monitor database activity.
This helps teams make sure the new PostgreSQL system stays stable, consistent, and ready for production use.
FAQ
How does Devart help with PostgreSQL autovacuum issues?
Devart tools help DBAs monitor database activity and find tables that may be growing too large or running slow queries. With this information, DBAs can adjust autovacuum settings and improve queries based on how the database is being used.
Can I migrate data from Oracle or MySQL to PostgreSQL easily?
Migration is usually done with tools such as pgloader, AWS Database Migration Service, or other tools that move data between databases. After the migration, dbForge Studio for PostgreSQL helps DBAs check the result by comparing schemas and data across databases.
Does the suite support multi-node database environments?
PostgreSQL handles replication between servers. Devart tools help DBAs compare schemas, check data, and monitor databases to make sure systems stay consistent across PostgreSQL servers.
