Compares how Oracle and PostgreSQL uniquely identify SQL queries and execution plans, focusing on SQL_ID vs query_id and PLAN_HASH_VALUE vs query_hash.
Explains a SQL Server edge case where automatic statistics updates don't always invalidate cached execution plans, focusing on system-created stats.
Explores the new ABORT_QUERY_EXECUTION query hint in SQL Server 2025 for blocking problematic queries via Query Store.
Explains the Optional Parameter Plan Optimization (OPPO) feature in SQL Server 2025, part of Intelligent Query Processing to mitigate parameter sniffing issues.
Explores the limitations of traditional pull queries in data systems and advocates for using materialized views and data duplication to improve performance.
Explores the shift from traditional pull queries to using materialized views and data duplication for better performance, format, and location in data systems.
PostgreSQL 19 introduces GROUP BY ALL, a new SQL feature that automatically groups by all non-aggregate columns, simplifying queries.
Explains how ToDictionaryAsync in Entity Framework Core retrieves entire database objects, impacting performance, and provides a solution using Select.
Demonstrates a 6x speedup for analytics queries using EDB Postgres Distributed's new analytics engine compared to the standard Postgres engine.
Explains a new PostgreSQL 19 feature that displays Memoize planner estimates in EXPLAIN output to help debug query plan choices.
A guide on documenting and organizing Kusto Query Language (KQL) code using comments, docstrings, and folders for better maintainability.
A guide to optimizing MySQL query performance in Spring applications using the Releem monitoring and analysis tool.
A guide to troubleshooting and improving performance in slow SQL Server applications using structured techniques.
Common issues with SQL date functions and practical solutions for developers and DBAs to avoid errors and improve query performance.
PostgreSQL 18 will improve EXPLAIN output by showing fractional row counts with two decimal digits for better query plan accuracy.
How to use DuckDB's COLUMNS expression to automatically rename fields when using SELECT * across joined tables, avoiding ambiguous column names.
Explores Apache Iceberg's advanced partitioning features, including hidden partitioning and transformations, for optimizing query performance in data lakes.
Introduces BigQuery's new GROUP BY ALL syntax, which automatically infers grouping keys from SELECT items to simplify complex SQL queries.
Explains a performance optimization technique for checking multiple row existence in SQL using LIMIT clauses, with benchmarks across RDBMS.
Compares partitioning techniques in Apache Hive and Apache Iceberg, highlighting Iceberg's advantages for query performance and data management.
