The article compares the performance of ClickHouse and PostgreSQL, highlighting their strengths and weaknesses in handling analytical queries and data processing. It emphasizes ClickHouse's efficiency in large-scale data management and real-time analytics, making it a suitable choice for high-performance applications.

The article discusses performance improvements in pgstream, a tool used for taking snapshots of PostgreSQL databases. It highlights the underlying challenges and solutions implemented to enhance the speed and efficiency of database snapshots, ultimately benefiting users with faster data access and reduced operational overhead.

PostgreSQL 18 has been released, featuring significant performance improvements through a new asynchronous I/O subsystem, enhanced query execution capabilities, and easier major-version upgrades. The release also introduces new features such as virtual generated columns, OAuth 2.0 authentication support, and improved statistical handling during upgrades, solidifying PostgreSQL's position as a leading open source database solution.

Pgline is a high-performance PostgreSQL driver for Node.js, developed in TypeScript, that implements Pipeline Mode, allowing for efficient concurrent queries with reduced CPU usage. Benchmark tests show Pgline outperforms competitors like Bun SQL, Postgresjs, and Node-postgres in terms of speed and resource efficiency. Installation and usage examples are provided to demonstrate its capabilities.

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.

Pipelining in PostgreSQL allows clients to send multiple queries without waiting for the results of previous ones, significantly improving throughput. Introduced in PostgreSQL 18, this feature enhances the efficiency of query processing, especially when dealing with large batches of data across different network types. Performance tests indicate substantial speed gains, underscoring the benefits of utilizing pipelining in SQL operations.