DuckDB community extensions bring Jev's plain-English conditions into SQL
DuckDB's blog covers community extensions that let you filter, classify and score rows such as 50,000 support tickets with plain-English conditions, instead of labeling data to train a classifier or sending each row to a chat LLM.
Jev & DuckDB: Plain-English Conditions in SQL 😎 🦆 Say you have a Parquet file of 50,000 support tickets and want to know which customers are angry. A `LIKE` pattern won’t find that. The usual options are to label data and train a classifier, or to send each row to a chat LLM and parse the text it returns. The first takes work up front. The second is slow and costs more per row. Jev – introduced by TypeSafe AI earlier this month – is a model that answers this kind of question with a typed value and a probability instead of a paragraph. Since then, a number of #DuckDB community extensions for Jev have been published that let you filter, classify, and score DuckDB rows with plain-English conditions. This post covers what Jev is, how the extensions work, and where to learn more: https://duckdb.org/2026/09/29/jev?utm_source=x&utm_medium=social #Jev