pgvector vs Green Vectors: How They Compare
pgvector and Green Vectors are different categories of technology. pgvector is an extension that adds vector search to PostgreSQL. Green Vectors is a reduction layer that eliminates redundant vectors before they are stored. They are not competitors. Green Vectors, delivered through Kitana, works alongside pgvector, and by reducing vector count it can extend how far pgvector scales before a dedicated database is needed.
Head-to-head comparison
| Dimension | pgvector | Green Vectors |
|---|---|---|
| Category | PostgreSQL vector extension | Vector reduction layer |
| Primary role | Adds vector search to Postgres | Reduces vector count before storage |
| Where it sits in the stack | Inside your Postgres database | The ingestion layer, before storage |
| Main benefit | Simplicity, no separate system | Extends scale, lowers storage |
| Relationship | Works with Green Vectors | Works alongside pgvector via Kitana |
What pgvector does
pgvector is a vector extension for PostgreSQL. Its advantage is simplicity: if your data already lives in Postgres, you avoid running a separate system. Its constraint is that performance and indexing can become limiting as vector counts grow large.
What Green Vectors does
Green Vectors applies patent-pending semantic transformation at ingestion to eliminate redundant vectors. In benchmarked workloads it reduced vector count by up to 99.5%, with storage falling from 260GB to 1.3GB at 15-million-vector scale, while improving search quality by up to 59%.
How they work together
Because pgvector becomes limiting as vector counts grow, reducing the number of vectors can keep pgvector viable at scales that would otherwise force a migration to a dedicated vector database. Kitana processes data through Green Vectors before it is written to Postgres, dramatically lowering the vector count pgvector has to handle.