At PGConf.EU, GitLab faced the challenge of deleting a 4 TB table in PostgreSQL with minimal impact. The table was archival, and the process involved considerations around WAL, caching, and ensuring no active reads were occurring.


Added to Fidup: ·postgr.es·1 min read
At PGConf.EU, GitLab faced the challenge of deleting a 4 TB table in PostgreSQL with minimal impact. The table was archival, and the process involved considerations around WAL, caching, and ensuring no active reads were occurring.
Igor Suhorukov's pg_vexec, a vectorized database, outperforms ClickHouse on Parquet queries and nearly matches it on MergeTree. After a month of development, it shows significant speed improvements.
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Percona Operator for MySQL 1.3.0 introduces autopilot tuning, zero-data-loss async failover, and encrypted point-in-time recovery, enhancing MySQL management on Kubernetes.
percona.com·Added

The study evaluated vector search performance by loading 990,000 OpenAI embeddings into six databases, building an HNSW index in each, and measuring various performance metrics. This helps developers understand vector search capabilities across different databases.
percona.com·Added

A tool that can extract data from raw database files without a running server is highly beneficial for database administrators. It allows offline data extraction from InnoDB, MyISAM, and MyRocks files, useful when the server is unavailable or for quick data recovery.
percona.com·Added

A study found that using a knowledge graph with SPARQL for AI agent memory queries resulted in higher accuracy compared to SQL. The choice between SQL and SPARQL should be based on personal experiments and specific needs.
postgr.es·Added

Real Python introduces embeddings and vector databases with ChromaDB, explaining how relevant documents can provide context for LLMs. The supplied excerpt covers vector fundamentals and NumPy operations; the tutorial targets ChromaDB 1.5 and Python 3.12+.
realpython.com·Added