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Improve database performance with connection pooling - Stack Overflow

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We tend to rely on caching solutions to improve database performance. Caching frequently-accessed queries in memory or via a database can optimize write/read performance and reduce network latency, especially for heavy-workload applications, such as gaming services and Q&A portals. But you can further improve performance by pooling users' connections to a database. Client users need to create a connection to a web service before they can perform CRUD operations. Most web services are backed by relational database servers such as Postgres or MySQL. With PostgreSQL, each new connection can take up to 1.3MB in memory. In a production environment where we expect to receive thousands or millions of concurrent connections to the backend service, this can quickly exceed your memory resources (or if you have a scalable cloud, it can get very expensive very quickly). Because each time a client attempts to access a backend service, it requires OS resources to create, maintain, and close connecti

We tend to rely on caching solutions to improve database performance. Caching frequently-accessed queries in memory or via a database can optimize write/read performance and reduce network latency, especially for heavy-workload applications, such as gaming services and Q&A portals. But you can further improve performance by pooling users' connections to a database. Client users need to create a connection to a web service before they can perform CRUD operations. Most web services are backed by relational database servers such as Postgres or MySQL. With PostgreSQL, each new connection can take

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