oelmekki/postgres-350d
Docker build of postgresql changing the dimension limit for the cube extension, raising it to 350
When working with vector data, such as word embeddings or other machine learning outputs, you often need to store and query these vectors in a database. This project provides a PostgreSQL database that removes the standard 100-dimension limit for its 'cube' extension, allowing you to work with vectors up to 350 dimensions. It's for data scientists, machine learning engineers, and researchers who need to store and operate on higher-dimensional vector data directly within their PostgreSQL database.
No commits in the last 6 months.
Use this if you need to store and perform operations on machine learning vectors or word embeddings with up to 350 dimensions directly within a PostgreSQL database, without encountering dimension limitations.
Not ideal if your vectors exceed 350 dimensions, as the 'pgvector' extension supports much higher dimensions (up to 16k) and might be a better fit.
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Last pushed
Oct 06, 2023
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