Shredding JSON columns gave Logfire up to 1000x faster queries

Shredding JSON columns gave Logfire up to 1000x faster queries(pydantic.dev)

8 points by acossta 4 hours ago | 5 comments

japgolly 25 minutes ago |

> Rather than storing all attributes in a single JSON column, we automatically extract the most frequently accessed attributes into separate, strongly typed columns.

I'm glad they made the discovery but this is DB 101

sgarland 2 hours ago |

It is hilarious to me when companies act like they've made some huge discovery that's been well-known to anyone working in DBs for the past decade, if not more.

JSON is slow as hell, both for serdes, and especially querying it. Use it sparingly, if at all. Normalization is not that hard, and it's trivial now with LLMs. Tell Claude you want your schema in BCNF, or 5NF if you're feeling froggy. Denormalize if and only if you have performance issues.

Neywiny 2 hours ago | |

Not even companies. I've seen this with colleagues. They wanted JSON parsing in a moderately embedded device. No thank you. Parse it elsewhere, give me the binary result

guites 2 hours ago | |

The point they make is that user data is dynamic, meaning you can't just blindly normalize every json attribute into its own column. The challenge is determining which attributes deserve "shredding" and doing it automatically iiuc

sans_souse 4 hours ago |

Let's just revert back 30 years and make the entire www plain text. What could possibly go wrong?