Understanding Database Indexes In PostgreSQL
- Pawel Dąbrowski tl;dr: “This article will help you organize your knowledge and remind you about good practices. SQL is a declarative language meaning it tells the database what we want to do but not how to achieve it. The database engine decides how to pull data. We can help the query planner by using indexes.”featured in #416
Nine Ways To Shoot Yourself In The Foot With PostgreSQL
- Phil Booth tl;dr: (1) Keep the default value for work\_mem. (2) Push application logic into Postgres functions and procedures. (3) Use lots of triggers. (4) Use NOTIFY heavily. And more.featured in #409
Postgres: The Graph Database You Didn't Know You Had
- Dylan Paulus tl;dr: Dylan shows us how we can store and query graph data structures in Postgres, something he did at his previous job to dynamically generate work instructions on a manufacturing line. “Based on parameters given, and rules defined on each edge, we could generate the correct document by traversing a graph stored entirely in Postgres.”featured in #402
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Just Use Postgres For Everything
- Stephan Schmidt tl;dr: "One way to simplify your stack and reduce the moving parts, speed up development, lower the risk and deliver more features in your startup is “Use Postgres for everything”. Postgres can replace - up to millions of users - many backend technologies, Kafka, RabbitMQ, Mongo and Redis among them." Stephan gives explicit examples how.featured in #375
Six Findings We Rely On When Managing PostgreSQL Indexes
- Billy Ceskavich tl;dr: "A rough guide on how to think through indexing strategy in most Postgres databases: (1) Every index has a read and write cost. Postgres considers these costs for each query to determine which indexes to use. (2) The more selective your index, the more efficient it becomes to read data from the table itself. But, more selective indexes (multicolumn indexes, sorted indexes, partial indexes) require specific query patterns to maximize this efficiency." And more.featured in #374
Scaling PostgresML To 1 Million Requests Per Second
- Lev Kokotov tl;dr: "In this post, we'll discuss how we horizontally scale PostgresML to achieve more than 1 million XGBoost predictions per second on commodity hardware.featured in #367
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6 Simple And Useful PostgreSQL Features That I Wish I Knew When I Started
- Marat Badykov tl;dr: "In this article, I will try to review 6 PostgreSql traits that seem to me the most important and easy-usable in a clear and brief way: (1) Identity. (2) COALESCE + NULLIF. (3) Grouping set, rollup, cube. (4) Common Table Expression. (5) Domains. (6) USING keyword.featured in #351
Postgres Full Text Search Is Awesome!
- Montana Low tl;dr: "With PostgresML, you can now skip straight to full on machine learning when you have the related data. You can load your feature store into the same database as your search corpus. Each data source can live in its own independent table, with its own update cadence, rather than having to reindex and denormalize entire documents back to ElasticSearch, or worse, large portions of the entire corpus, when a single thing changes."featured in #349