PostgreSQL DBA

https://www.postgresql.org/docs/current/storage-toast.html Understanding about TOAST Join PostgreSQL

https://towardsdatascience.com/how-to-build-a-data-lake-from-scratch-part-2-connecting-the-components-1bc659cb3f4f How to build a data lake from scratch — Part 2: Connecting the components

https://towardsdatascience.com/how-to-build-a-data-lake-from-scratch-part-1-the-setup-34ea1665a06e How to build a data lake from scratch — Part 1: The setup

https://www.starburst.io/blog/scaling-up-when-to-migrate-from-postgresql-to-a-data-lake/ Scaling Up: When to Migrate from PostgreSQL to a Data Lake

https://www.enterprisedb.com/blog/what-is-pgvector What is pgvector and How Can It Help You?

https://www.highgo.ca/2020/08/10/postgresql-high-availability-the-considerations-and-candidates/ PostgreSQL High Availability: The Considerations and Candidates

https://pgstatsinfo.sourceforge.net/documents/statsinfo_old/pg_statsinfo2.2.html pg_statsinfo monitors an instance of PostgreSQL server

https://medium.com/@sumeet.k.shukla/postgresql-architecture-6df259dc1145 Understanding about PostgreSQL Architecture!

What is parallel querying in PostgreSQL? Parallel querying is a technique in PostgreSQL that allows you to create query plans that can leverage multiple CPUs to answer queries more efficiently. This technique is particularly well-suited when the query involves scanning a lot of data but returning a few rows, for example, aggregate calculations.

https://www.postgresql.org/docs/current/geqo-pg-intro.html Genetic Query Optimization (GEQO)

How can you handle errors in PostgreSQL? There are two main ways to address errors in PostgreSQL: Callback functions can be developed to handle warning and error conditions. In this case, you can specify a certain behavior in case of errors and warnings in your queries using the WHENEVER command. Detailed information about the error or warning can be obtained from the sqlca variable. This variable provides detailed information when errors and warnings arise during execution.

How can you improve query performance in PostgreSQL? There are multiple strategies to increase query performance, including: Using indexing, especially in queries that involve WHERE clauses; Writing efficient SQL statements to reduce processing overhead, for example, by avoiding unnecessary columns in the SELECT statement. Implementing partitioning for large tables. Optimizing memory usage by tuning server parameters to match hardware specifications. Especially when dealing with large databases, improving your query performance is crucial to avoid undesired bottlenecks. Check out our Improving Query Performance in PostgreSQL Course to become a query wizard.