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Does machine learning for database optimization work in the real world?
Lessons learned from OtterTune, an AI-powered database tuning service
Database Management Systems (DBMSs) are complex software that require precise tuning to achieve optimal performance on specific hardware and workloads. However, manual tuning by experienced administrators becomes impractical for large-scale DBMS deployments. To address this challenge, there has been a growing trend in both academia and industry to employ machine learning (ML) for automatic data...
Everything you want to know about Postgres autovacuum
Best practices for monitoring and tuning autovacuum in Postgres
Because of the design and implementation of Multi-Version Concurrency Control (MVCC) in Postgres, the old data accumulates during updates. Hence, the indispensable role of Postgres autovacuum, responsible for garbage collection of dead tuples, becomes crucial for ensuring database performance. However, effectively monitoring and tuning autovacuum is a non-trivial task. In this presentation, I w...
The Part of PostgreSQL I Hate the Most
what are the drawbacks of MVCC in Postgres and how to optimize it
Postgres is awesome. It is currently the fourth most popular database (source: DB-Engines), and its popularity continues to grow as strong as ever due to several factors: its rich set of features, mixing object storage and relational capabilities; its extensibility; and its status as an open source project. But as much as we love PostgreSQL, there are certain aspects about it that are not that ...