10 Common Mistakes Made With Postgres

January 30th, 2023

0 min read

Postgres 101

PostgreSQL is a powerful and widely-used open-source relational database management system (RDBMS). However, as with any piece of complex software, there are common mistakes that users can make when working with it.

In this blog post, we will discuss ten of the most common mistakes that people make with Postgres, and why it is important to avoid them. By understanding and avoiding these mistakes, you can ensure that your PostgreSQL database is operating efficiently and effectively.

  1. Not properly configuring PostgreSQL's memory usage: It is important to configure PostgreSQL's memory usage properly to ensure that the server has enough memory to operate efficiently. If the server is not given enough memory, it may become slow or even crash. A general recommendation is to start by giving Postgres 25% of the available memory.

  2. Not regularly vacuuming and analyzing tables: PostgreSQL uses a technique called "vacuuming" to clean up deleted or outdated rows in tables. If this is not done regularly, the database can become bloated and slower to query. It is also important to regularly analyze the tables to update PostgreSQL's statistics, which are used to plan efficient queries. You can read more about how to regularly vacuum and analyze your tables in our docs.

  3. Not using indexes effectively: Indexes are used to speed up queries by allowing the database to quickly locate rows that match certain criteria in the query WHERE or JOIN clauses. However, if added indexes are not actually needed, they can slow down writes to your tables. It is important to carefully consider which columns to index and to avoid over-indexing. Using query EXPLAIN plans can help you with this.

  4. Using the wrong data types for columns: Choosing the wrong data type for a column can lead to inefficient storage and slow queries. For example, using a character data type with a fixed length (e.g. char(10)) when a variable length data type (e.g. varchar) would be more appropriate.

  5. Not using foreign keys for data integrity: Foreign keys are used to enforce relationships between tables and maintain the integrity of the data. Failing to use foreign keys can lead to data inconsistencies and errors when records in one table are deleted and dependent records in another table are left behind orphaned. Foreign keys between these dependent tables prevent records from being deleted if they are still referenced.

  6. Not properly handling connection pooling: Connection pooling is a technique used to reduce the overhead of establishing new connections to the database. If connection pooling is not used or configured properly, it can lead to performance issues when too many connections are opened to the database. PgBouncer is a very popular and performant connection pooler for Postgres.

  7. Not using prepared statements and parameterized queries: Prepared statements and parameterized queries can improve the security and performance of a database by preventing SQL injection attacks and allowing the database to cache query plans. For queries that are repeated frequently using a prepared statement can improve query performance.

  8. Not using transactions for database updates: Transactions are used to ensure that a series of database updates are completed atomically as a single unit of work. If a transaction is not used, it is possible for the updates to be applied partially, leading to data inconsistencies.

  9. Not backing up the database regularly: It is important to regularly back up the database to protect against data loss due to hardware failures, human error, or other unexpected events. Most Postgres hosting providers offer routine database backups that should be enabled.

  10. Not monitoring and analyzing performance: Regularly monitoring and analyzing the performance of the database can help identify and troubleshoot issues, as well as optimize queries and configuration settings for better performance.

Using a monitoring tool such as Postgres Monitor can help with some of these common PostgreSQL mistakes through our health dashboards, dynamic recommendations and alerts.

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