Which is more popular, pgvector or zvec?

pgvector has more GitHub stars (23,226 vs 16,057).

Which is more actively developed, pgvector or zvec?

zvec had more commits in the last 90 days (151 vs 128).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

pgvector is growing faster: +435 GitHub stars in the last 30 days vs +270 for zvec.
Pick pgvector for: open-source vector similarity search for Postgres. Pick zvec for: a lightweight, lightning-fast, in-process vector database.

From GitHub data refreshed daily.

Open-source vector similarity search for Postgres

zvecopen-source

A lightweight, lightning-fast, in-process vector database

+Native PostgreSQL integration preserves ACID compliance, transactions, and allows complex JOINs between vector and relational data
+Supports multiple vector types (single/half-precision, binary, sparse) and distance metrics (L2, cosine, inner product, Hamming, Jaccard)
+Wide ecosystem compatibility with any language that has a Postgres client and available through multiple installation methods

-Requires PostgreSQL expertise and may have steeper learning curve compared to dedicated vector databases
-Installation complexity varies by platform, especially on Windows systems
-Performance may not match specialized vector databases for very large-scale vector workloads

•RAG (Retrieval Augmented Generation) applications where embeddings need to be stored alongside document metadata and user data
•E-commerce recommendation systems that combine vector similarity with product catalog data and user preferences
•Semantic search applications where vector queries need to be combined with traditional filters and business logic

Which is more popular, pgvector or zvec?: pgvector has more GitHub stars (23,226 vs 16,057).
Which is more actively developed, pgvector or zvec?: zvec had more commits in the last 90 days (151 vs 128).
Should I use pgvector or zvec?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.