Exploring Alternatives to SQL Server Query Store in PostgreSQL

In PostgreSQL, the closest alternative to SQL Server’s Query Store feature, which allows for capturing query plans and performance metrics for historical analysis, is the combination of the pg_stat_statements extension with additional logging and monitoring tools. While PostgreSQL does not have a built-in feature identical to Query Store, pg_stat_statements and other tools can provide deep insights into query performance and help with performance tuning and troubleshooting.

pg_stat_statements

The pg_stat_statements module is included with PostgreSQL and provides a means to track execution statistics of all SQL statements executed by the server, not just queries. This includes the number of times a statement was executed, the total time spent in the database for those executions, and more.

To use pg_stat_statements, you need to:

1. Enable the extension in your database:
   
   Shell

   CREATE EXTENSION pg_stat_statements;

   1 2	CREATE EXTENSION pg_stat_statements;

2. Add it to the shared_preload_libraries in your postgresql.conf file to ensure it’s loaded at server start:
   
   Shell

   shared_preload_libraries = 'pg_stat_statements'

   1 2	shared_preload_libraries = 'pg_stat_statements'

   
   After changing the configuration, you’ll need to restart your PostgreSQL server.
3. Query the pg_stat_statements view to analyze query performance:
   
   Shell

   SELECT query, calls, total_time, rows, 100.0 * shared_blks_hit / nullif(shared_blks_hit + shared_blks_read, 0) AS hit_percent FROM pg_stat_statements ORDER BY total_time DESC;

   1 2 3 4

   SELECT query, calls, total_time, rows, 100.0 * shared_blks_hit / nullif(shared_blks_hit + shared_blks_read, 0) AS hit_percent FROM pg_stat_statements ORDER BY total_time DESC;

Additional Monitoring and Logging

For a more comprehensive solution akin to SQL Server’s Query Store, consider integrating pg_stat_statements with other PostgreSQL features and third-party tools:

• Logging: PostgreSQL’s extensive logging capabilities can be configured to log long-running queries or all queries, among other options. The logs can then be analyzed using tools like pgBadger.
• Extensions and External Tools: Consider using extensions like pg_qualstats, pg_stat_kcache, and auto_explain for deeper insights into query execution and performance issues. External monitoring tools like Prometheus with Grafana, or commercial platforms like pganalyze, provide powerful interfaces for visualizing and analyzing PostgreSQL performance data over time.
• Custom Views and Functions: You can create custom views or functions that aggregate and report performance data tailored to your specific needs, combining data from pg_stat_statements with other PostgreSQL statistics.

While PostgreSQL’s approach requires a bit more setup and integration work compared to SQL Server’s Query Store, it offers flexibility and powerful options for monitoring query performance and planning optimizations. The key is to leverage the pg_stat_statements extension as the foundation of your query performance analysis strategy and integrate it with other tools and practices for a comprehensive solution.