# pgvector: what AI models say (September 2026)

Source: Memetik Index, https://www.memetik.ai/vendors/pgvector
Website: https://www.enterprisedb.com

pgvector was named in 49 of 50 AI answers across 1 category. Best position: Vector databases, 98% answer share, ranked #1, named first in 32%.

## What pgvector is

pgvector is a PostgreSQL extension for applications that need to store and compare vectors. It is used in recommendation systems, image search, natural language processing, content-based filtering and other similarity-based AI tasks.

It adds vector data types to PostgreSQL, allowing embedding data to be stored alongside other application data. It performs vector similarity searches to find related records, and can index vectors with HNSW or IVFFlat indexes.

(From pgvector's own website, read 2026-09-02.)

## By category

| Category | Rank | Answer share | Named first | Models |
|---|---|---|---|---|
| Vector databases (https://www.memetik.ai/index/vector-databases) | #1 of 16 | 98% | 32% | GPT-5.6 Sol, ChatGPT, GPT-5.6 Luna, Claude Opus 5, Claude, Claude Fable 5, Gemini, Gemini 3.5 Flash, Perplexity, Sonar Reasoning Pro |

## What the models said

> "Bottom line If you haven’t provided any additional constraints: > Start with pgvector if you already run PostgreSQL."
> — GPT-5.6 Sol, Vector databases

> "Highlighted as the best free and open‑source vector database for RAG and “best value” when you already run Postgres."
> — Sonar Reasoning Pro, Vector databases

> "Choose pgvector if your workload is moderate and you want vectors to live alongside relational data in PostgreSQL."
> — Perplexity, Vector databases

> "PostgreSQL + pgvector This is often the best architectural choice when the application already relies on Postgres."
> — GPT-5.6 Luna, Vector databases