In this blog, I will be focusing on common I/O problems PostgreSQL databases can encounter in real-time production environments. Any real-time data operation is I/O bound, it is imperative to ensure the database is I/O tuned. This means, database processes are spending more time either writing to or reading from the disk. Most of the times, database performance problems are caused mainly due to high I/O. Tuning the Input / Output operations of PostgreSQL is essential, especially in a high-transactional environment like OLTP or in a Data warehousing environment with complex data analysis on huge size data sets. One of the significant areas I would like to focus on in this blog is how to tune PostgreSQL I/O (Input / Output) performance. So that’s a lot of potential areas which can cause performance problems. No connection pooling in place, which cause applications to make huge number of connections in an uncontrollable manner.Inefficient capacity planning resulting in inadequately dimensioned infrastructure.Bad database maintenance with no proper statistics in place.Queries performing full-table-scans on big tables due to improper Indexing.Badly written queries with bad joins, logic etc.What can Cause Database Performance to Degrade? Database performance can go bad for various reasons such as infrastructure dimensioning, inefficient database maintenance strategy, poor SQL code or badly configured database processes that fail to utilize all the available resources – CPU, memory, network bandwidth and disk I/O. Well, the accomplishment of good database performance depends on various factors. To ensure that databases perform at the expected scale with expected response times, there is a need for some performance engineering. PostgreSQL I/O is quite reliable, stable and performant on pretty much any hardware, including even cloud. PostgreSQL is one of the most popular open-source databases in the world and has successful implementations across several mission-critical environments across various domains, using real-time high-end OLTP applications performing millions and billions of transactions per day.
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