PostgreSQL, a powerful open-source relational database, offers several options to improve query caching and query performance when self-hosted.
Shared Memory Caching: Configure the
shared_buffersparameter in the
postgresql.conffile to allocate more memory for caching data blocks. A good value for this would be 25% of total amount of memory.
Add Missing Indexes: Another way to improve cache hit rate would be to add any missing indexes for common or expensive queries. Use query
explainplans and query monitoring tools such as
pg_stat_statementsor Postgres Monitor to identify missing indexes.
Table Partitioning: Partitioning large tables can also increase query performance by reducing the data that needs to be scanned and loaded into memory for certain queries.
Query Caching: Use other tools such as Redis or Memcached to cache query results outside of the database to reduce database load. This can be implemented at the application layer, caching frequently executed queries and their results in memory.
Scale Up Your Database: If the above options do not improve query cache hit rates enough, you should upgrade your database instance size to add additional memory (ie RAM) to support your query workload.
The best caching strategy can vary based on the specific use case, database size, query nature, and available hardware. Combining different caching methods often yields the best performance improvements.
It's recommended to benchmark and test caching strategies for effectiveness with your workload before deploying to a production environment. Adjust configurations and strategies based on performance metrics and specific requirements.