Best of PostgreSQL — January 2024
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Community Picks·2y
1 billion rows challenge in PostgreSQL and ClickHouse
This post discusses the process of ordering 1 billion rows in Java using PostgreSQL and ClickHouse. It covers generating the data, setting up local databases, loading the data, running queries, and comparing the results. The post highlights the faster performance of ClickHouse compared to PostgreSQL for querying directly from a CSV file.
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Supabase·2y
Getting started with Laravel and Postgres
Learn how to get started with Laravel and Postgres using Supabase as an alternative to Heroku. Set up a new Laravel application, install the authentication template, configure the Postgres connection details, run database migrations, and start the app.
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TigerData (Creators of TimescaleDB)·2y
PostgreSQL vs MySQL: Which to Choose and When
Comparison of PostgreSQL and MySQL as relational databases. Explore their similarities, strengths, and weaknesses. Learn about their features and decide the right database solution based on your project requirements, scale, and data operations.
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Community Picks·2y
How Cloudflare Was Able to Support 55 Million Requests per Second With Only 15 Postgres Clusters
Cloudflare achieved the ability to support 55 million requests per second using only 15 Postgres clusters. They utilized PgBouncer as a connection pooler to manage Postgres connections, avoided the thundering herd problem, employed high-performance bare metal servers instead of cloud infrastructure, used the TCP Vegas congestion avoidance algorithm for concurrency management, ordered queries at the PgBouncer layer, and ensured high availability with the Stolon cluster manager.
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Community Picks·2y
How the PostgreSQL optimizer works to speed up queries
This post explains how the PostgreSQL optimizer works and highlights some important techniques it uses to speed up queries, such as constant folding, function inlining, join optimization, join order determination, join pruning, and optimized sorting for ORDER BY.
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Adam Johnson·2y
PostgreSQL: Full text search with the “websearch” syntax
PostgreSQL's powerful full text search feature supports the websearch syntax, which is forgiving and user-friendly. It allows individual word matching, double-quoted phrase matching, OR conditions, and negating matching. This post explains the syntax and how to use it in queries. It also mentions the integration of websearch in Django.
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