PostgreSQL Performance Archives - Page 5 of 6 - The Data Transformation Company

PostgreSQL Non-Clustered Indexes: Impact of Non-Covering Indexes on Query Performance

Impact of Non-Covering Non-Clustered Indexes on Query Performance in PostgreSQL If a non-clustered index (also known as a secondary index in PostgreSQL) is useful for quickly finding one or more records but does not cover […]

Minimizing Performance Impact: Best Practices for PostgreSQL Tracing and Monitoring

When tracing or monitoring tools are enabled in PostgreSQL, it can introduce some overhead and potentially slow down database performance. This is because tracing mechanisms such as logging, detailed monitoring, or execution profiling require additional […]

Implementing a Custom date_bucket() Function in PostgreSQL for Timestamp Bucketing

PostgreSQL date_bucket Function The date_bucket() function in PostgreSQL is a powerful tool for time series analysis. It allows you to group timestamps into fixed-size intervals, often referred to as “buckets.” This grouping is useful for […]

PostgreSQL Aggregate Functions: A Comprehensive Guide

PostgreSQL is equipped with a robust suite of statistical functions that are essential for performing detailed data analysis directly within the database. These functions allow users to calculate various statistical measures, such as averages, variances, […]

Optimizing Query Performance: Tips for Troubleshooting PostgreSQL Statistics and Cost Estimation

Troubleshooting statistics and cost estimation in PostgreSQL is crucial for understanding and optimizing query performance. PostgreSQL uses statistics to make informed decisions about the best way to execute queries, including which indexes to use and […]

Long-Running Queries in PostgreSQL: Troubleshooting Queries and Wait Events

Troubleshooting long-running queries in PostgreSQL and identifying wait events, along with insights into application and session operations, involves several steps. This process helps in pinpointing the root cause of performance issues and in formulating appropriate […]

PostgreSQL Materialized Path: Implementing the Model Step-by-Step

The Materialized Path model is a strategy for representing hierarchical data within a relational database system like PostgreSQL. It involves storing the entire path to a node within a tree as a single column value […]

PostgreSQL for SQL Server DBAs – What is an alternative to sys.dm_exec_query_stats in the PostgreSQL world?

PostgreSQL for SQL Server DBAs The sys.dm_exec_query_stats Dynamic Management View (DMV) in Microsoft SQL Server provides performance statistics for cached query plans. It allows database administrators and developers to monitor and analyze SQL query performance, […]

Adaptive Joins in PostgreSQL 16 (mimicked feature)

Introduction PostgreSQL does not natively offer "Adaptive Hash Joins" as a built-in feature for query execution.Instead, the query planner selects join methods, such as nested loop, hash join, or merge join, during plan generation.Additionally, it [...]

Troubleshooting PostgreSQL JOIN Performance: A Guide for Query Optimization

PostgreSQL environment is unique, so these guidelines should be adapted and tested according to your specific context. Regular monitoring and a thorough understanding of your data and query patterns are key to maintaining optimal JOIN performance.

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