Episodes on how best to scale your PostgreSQL relational database.
In this episode of Scaling Postgres, we discuss a new extension that promises substantially faster text search and ranking, an AI content storm, how to work with money and the fastest way to stop Postgres.
In this episode of Scaling Postgres, we cover a deep dive into indexes from a presentation that includes a decision tree of sorts, how to convert to partitioned tables once you have hundreds of millions of rows and detail about the new pg_stat_io view.
In this episode of Scaling Postgres, we discuss whether something is 23 times faster or 1.1 times faster. We also discuss the release of Timescale Vector and whether you can build a queue on Postgres.
In this episode of Scaling Postgres, we discuss how to get 222 times faster analytical queries with columnar storage, a Postgres 16 feature review, the birth of a feature and fuzzy search.
In this episode of Scaling Postgres, we discuss the release of Postgres 16, a Postgres meme, storing files or base64 strings and sharding intelligently.
In this episode of Scaling Postgres, we discuss the benefits and disadvantages of HNSW indexes for working with vector data, configuring vacuum to reduce bloat and optimize performance, the new options available for \watch and all about connections.
In this episode of Scaling Postgres, we discuss the release of Postgres 16 RC1, implementing bi-directional replication, different ways you can set up Postgres parameters and how to handle polymorphism and foreign keys.
In this episode of Scaling Postgres, we discuss how pgbouncer can impact a TPS benchmark, partition-wise join & aggregate performance, partitioning a table with billions of rows and cool Postgres 16 features.
In this episode of Scaling Postgres, we discuss how to squeeze the most out of your database, achieving one million connections to Postgres, how to use indexes with LIKE and pgvector HNSW index performance.
In this episode of Scaling Postgres, we discuss new Postgres releases, taking the 2023 State of PostgreSQL survey, partitioning vs. sharding and the fastest way to do bulk loads.