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

PostgreSQL 15 Released!

tl;dr: "PostgreSQL 15 builds on the performance improvements of recent releases with noticeable gains for managing workloads in both local and distributed deployments, including improved sorting. This release improves the developer experience with the addition of the popular MERGE command, and adds more capabilities for observing the state of the database."

featured in #360

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

My Notes On GitLab Postgres Schema Design

- Shekhar Gulati tl;dr: "My motivation to understand the schema of a big project like Gitlab was to compare it against schemas I am designing and learn some best practices from their schema definition. I can surely say I learnt a lot."

featured in #338

Speeding Up Sort Performance In Postgres 15

- David Rowley tl;dr: David explores each of the 4 improvements in PostgreSQL 15 that make sort performance go faster: (1) Improvements sorting a single column. (2) Reduce memory consumption by using generation memory context. (3) Add specialized sort routines for common datatypes. (4) Replace polyphase merge algorithm with k-way merge.

featured in #321

Postgres Auditing In 150 lines Of SQL

- Oliver Rice tl;dr: "Data auditing is a system that tracks changes to tables' contents over time. PostgreSQL has a robust set of features which we can leverage to create a generic auditing solution in 150 lines of SQL."

featured in #303

How We Optimized PostgreSQL Queries 100x

- Vadim Markovtsev tl;dr: Some of the tricks we used to speed up SELECT-s in PostgreSQL: LEFT JOIN with redundant conditions, VALUES, extended statistics, primary key type conversion, CLUSTER, pg\_hint\_plan + bonus.

featured in #298