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Databases & Data

The most popular blog posts about databases & data on Hacker News. 4,224 posts.

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2133

Migrating bajillions of database records at Stripe

There are roughly ten thousand bajillion (to the nearest bajillion) merchants registered with Stripe. We recently finished a Very Big Migration of Large Amounts Of Data between several database tables for every single one of them, without losing any of it, without any downtime, mis-reads or mis-writes, whilst running…

2138

Introduction to Hacking PostgreSQL (2007)

Gavin Sherry and I have presented several versions of a tutorial introduction on how to modify the PostgreSQL source code. The original version was given at the PostgreSQL Anniversary Summit in June of 2006. Gavin has since given a revised version of the talk (at LCA 2007), as have I (at PgCon 2007).

2142

Debunking Misleading Benchmarks Of Redshift vs BigQuery

Publishing misleading performance benchmarks is a classic old guard marketing tactic. It’s not surprising to see old guard companies (like Oracle) doing this, but we were kind of surprised to see Google take this approach, too. So, when Google presented their BigQuery vs. Amazon Redshift benchmark results at a private…

2146

NumPy 1.20

This NumPy release is the largest so made to date, some 684 PRs contributed by 184 people have been merged. See the list of highlights below for more details. The Python versions supported for this release are 3.7-3.9, support for Python 3.6 has been dropped. Highlights are

2152

SQLite Begin Concurrent

Usually, SQLite allows at most one writer to proceed concurrently. The BEGIN CONCURRENT enhancement allows multiple writers to process write transactions simultanously if the database is in "wal" or "wal2" mode, although the system still serializes COMMIT commands.

2153

NanoGPT Slowrun: 10x Data Efficiency with Infinite Compute

We've achieved 10x data efficiency with NanoGPT Slowrun within a few weeks. An ensemble of 1.8B parameter models (18B total params) trained on 100M tokens matches what would normally require 1B tokens with a standard LM baseline. Data efficiency matters because compute grows much faster than data . Since our current…