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Topics /
Databases & Data
The most popular blog posts about databases & data on Hacker News. 4,222 posts.
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Function pipelines: Building functional programming into PostgreSQL
Function pipelines allow you to analyze data by composing multiple functions in SQL and express complex logic in PostgreSQL in a cleaner way.
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Analyzing Cryptocurrency Markets Using Python
A data-driven approach to cryptocurrency (Bitcoin, Ethereum, Litecoin, Ripple etc.) market analysis and visualization using Python.
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What ORMs Have Taught Me: Just Learn SQL (2014)
I’ve come to the conclusion that, for me, ORMs are more detriment than benefit. In short, they can be used to nicely augment working with SQL in a program, but they should not replace it.
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Scaling PostgreSQL to power 800M ChatGPT users
An inside look at how OpenAI scaled PostgreSQL to millions of queries per second using replicas, caching, rate limiting, and workload isolation.
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What is Differential Privacy?
Yesterday at the WWDC keynote, Apple announced a series of new security and privacy features, including one feature that’s drawn a bit of attention — and confusion. Specifically, Apple …
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What GPT-OSS leaks about OpenAI's training data
OpenAI recently released their open-weights model. Here we'll discuss how that inevitably leaks some information about their model training stack, and, on the way, show that GPT-5 was trained on phrases from adult websites....
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Tracking SQLite Database Changes in Git
Note : This post stirred up some interesting discussions on HackerNews and Lobste.rs .
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Turning SQLite into a Distributed Database
mvSQLite is the open-source , SQLite-compatible distributed database. We decoupled SQLite's storage layer onto FoundationDB to offer massive yet "bottomless" scalability, point-in-time reads, and the strictest level of consistency.
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Python is not a great language for data science
It may be a good language for data science, but it’s not a great one.
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Introduction to Apache Airflow
Airflow is a platform to programmatically author, schedule, and monitor workflows. In this blog we will underestand the basics of airflow
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Command-line tools for data science
Blog article by Jeroen Janssens. Sep 19, 2013. 21 min read. Data science is OSEMN (pronounced as awesome). That is, it involves Obtaining, Scrubbing, Exploring, Modelling, and iNterpreting data. As a data scientist, I spend quite a bit of time on the command-line, especially when there’s data to be obtained, scrubbed…
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The Great Migration from MongoDB to PostgreSQL
How Infisical migrated from MongoDB to PostgreSQL.
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We replaced Redis with MySQL for inventory reservations and it scaled
How we used SKIP LOCKED, composite primary keys, and connection visibility to hit our scale targets.
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Interesting data structures: the BK-tree
A BK-tree is a tree data structure specialized to index data in a metric space . A metric space is essentially a set of objects which we equip with a distance function $d(a, b)$ for every pair of elements $(a, b)$. This distance function must satisfy a set of axioms in order to ensure it’s well-behaved. The exact…
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Grok 4.6 scores 61 on the Artificial Analysis Intelligence Index
SpaceXAI returns to the intelligence frontier with strengths in agentic performance and cost efficiency
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Useful Unix commands for exploring data
While dealing with big genetic data sets I often got stuck with limitation of programming languages in terms of reading big files. Also so...
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Working with time in Postgres
A massive amount of reporting queries, whether really intensive data analysis, or just basic insights into your business involving looking at data over a certain time period. Postgres has really rich support for dealing with time out of the box, something that’s often very underweighted when dealing with a database…
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How does database sharding work?
Learn what database sharding is, how sharding works, and some common sharding frameworks and tools.
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Unlearning descriptive statistics
If you've ever used an arithmetic mean, a Pearson correlation or a standard deviation to describe a dataset, I'm writing this for you. Better numbers exist to summarize location, association and spread: numbers that are easier to interpret and that don't act up with wonky data and outliers.
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How to visualize decision trees
Decision trees are the fundamental building block of gradient boosting machines and Random Forests(tm), probably the two most popular machine learning models for structured data. Visualizing decision trees is a tremendous aid when learning how these models work and when interpreting models. Unfortunately, current…
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Amazon Aurora Now Available
We announced Amazon Aurora last year at AWS re:Invent (see Amazon Aurora – New Cost-Effective MySQL-Compatible Database Engine for Amazon for more info). With storage replicated both within and across three Availability Zones, along with an update model driven by quorum writes, Amazon Aurora is designed to deliver…