# pgvector: Fewer dimensions are better

DevFeed: [pgvector: Fewer dimensions are better](<https://devfeed.tech/articles/pgvector-fewer-dimensions-are-better-371.md>)

Original publisher: [Read original article](<https://supabase.com/blog/fewer-dimensions-are-better-pgvector>)

Author: Greg Richardson; Oliver Rice; Egor Romanov

Published: 2023-08-03T07:00:00Z

Content type: article

Language: en

Sources: [Supabase Blog](<https://devfeed.tech/sources/supabase-blog.md>)

Topics: [Embeddings](<https://devfeed.tech/topics/embeddings.md>), [Supabase](<https://devfeed.tech/topics/supabase.md>), [AI search](<https://devfeed.tech/topics/ai-search.md>), [hugging face](<https://devfeed.tech/topics/hugging-face.md>)

Tags: [compute](<https://devfeed.tech/tags/compute.md>), [embedding](<https://devfeed.tech/tags/embedding.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [index](<https://devfeed.tech/tags/index.md>), [information-retrieval](<https://devfeed.tech/tags/information-retrieval.md>), [openai](<https://devfeed.tech/tags/openai.md>), [performance](<https://devfeed.tech/tags/performance.md>), [pgvector](<https://devfeed.tech/tags/pgvector.md>), [provisioning](<https://devfeed.tech/tags/provisioning.md>), [vectors](<https://devfeed.tech/tags/vectors.md>)

## AI overview

This article explains why using embedding vectors with fewer dimensions can improve pgvector performance. It covers vector storage in Postgres, similarity indexes, memory and compute requirements, and the scaling challenges of high-dimensional embeddings.

## Source excerpt

Increase performance in pgvector by using embedding vectors with fewer dimensions