PostgreSQL 18 introduces significant improvements to the btree_gist extension, primarily through the implementation of sortsupport, which enhances index building efficiency. These updates enable better performance for use cases such as nearest-neighbour search and exclusion constraints, offering notable gains in query throughput compared to previous versions.

Discord outlines its innovative approach to indexing trillions of messages, focusing on the architecture that enables efficient retrieval and storage. The platform leverages advanced technologies to ensure users can access relevant content quickly while maintaining high performance and scalability.

The article explores the use of custom ICU collations with PostgreSQL's citext data type, highlighting performance comparisons between equality, range, and pattern matching operations. It concludes that while custom collations are superior for equality and range queries, citext is more practical for pattern matching until better index support for nondeterministic collations is achieved.

The article discusses the advantages of indexing JSONB data types in PostgreSQL, emphasizing improved query performance and efficient data retrieval. It provides practical examples and techniques for creating indexes, as well as considerations for maintaining performance in applications that utilize JSONB fields.

The Marginalia Search index has undergone significant redesign to enhance performance through new data structures optimized for modern hardware, increasing the index size from 350 million to 800 million documents. The article discusses the challenges faced in query performance and the implications of NVMe SSD characteristics, as well as the transition from B-trees to deterministic block-based skip lists for improved efficiency in document retrieval.

The article discusses techniques for efficiently indexing codebases using cursors, which can significantly enhance navigation and searching capabilities. It emphasizes the importance of structured indexing to improve the speed and accuracy of code retrieval, making it easier for developers to work with large codebases.

ClickHouse introduces its capabilities in full-text search, highlighting the efficiency and performance improvements it offers over traditional search solutions. The article discusses various features, including indexing and query optimization, that enhance the user experience for searching large datasets. Additionally, it covers practical use cases and implementation strategies for developers.

PostgreSQL's Index Only Scan enhances query performance by allowing data retrieval without accessing the table heap, thus eliminating unnecessary delays. It requires specific index types and query conditions to function effectively, and the concept of a covering index, which includes fields in the index, further optimizes this process. Understanding these features is crucial for backend developers working with PostgreSQL databases.

User-defined indexes can be embedded within Apache Parquet files, enhancing query performance without compatibility issues. By utilizing existing footer metadata and offset addressing, developers can create custom indexes, such as distinct value indexes, to improve data pruning efficiency, particularly for columns with limited distinct values. The article provides a practical example of implementing such an index using Apache DataFusion.

Data types significantly influence the performance and efficiency of indexing in PostgreSQL. The article explores how different data types, such as integers, floating points, and text, affect the time required to create indexes, emphasizing the importance of choosing the right data type for optimal performance.

The article explores the differences in indexing between traditional relational databases and open table formats like Apache Iceberg and Delta Lake, emphasizing the challenges and limitations of adding secondary indexes to optimize query performance in analytical workloads. It highlights the importance of data organization and auxiliary structures in determining read efficiency, rather than relying solely on traditional indexing methods.

Understanding when to rebuild PostgreSQL indexes is crucial for maintaining database performance. The decision depends on index type, bloat levels, and performance metrics, with recommendations to use the `pgstattuple` extension to assess index health before initiating a rebuild. Regular automatic rebuilds are generally unnecessary and can waste resources.