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Why "negative vectors" can't delete data in FAISS – but weighted kernels can

RAG accuracy jumped from 10% to 60% when I added outcome scoring

Show HN: Misata – synthetic data engine using LLM and Vectorized NumPy

Show HN: Linggen – A local-first memory layer for your AI (Cursor, Zed, Claude)

Show HN: A local-first memory store for LLM agents (SQLite)

7 Years, 2 Rebuilds, 40K+ Stars: Milvus Recap and Roadmap

Indexing 100M vectors in 20 minutes on PostgreSQL with 12GB RAM

A vector graphics workstation from the 70s

Hachi: An Image Search Engine

Pinecone Introduces Dedicated Read Nodes in Public Preview for Predictable Vector Workloads

Pinecone recently announced the public preview of Dedicated Read Nodes (DRN), a new capacity mode for its vector database designed to deliver predictable performance and cost at scale for high-throughput applications such as billion-vector semantic search, recommendation systems, and mission-critical AI services. By Craig Risi

Article: NextGen Search - Where AI Meets OpenSearch Through MCP

In this article, authors Srikanth Daggumalli and Arun Lakshmanan discuss next-generation context-aware conversational search using OpenSearch and AI agents powered by Large Language Models (LLMs) and Model Context Protocol (MCP). By Srikanth Daggumalli, Arun Lakshmanan

Agentic Postgres: Postgres for Agentic Apps with Fast Forking and AI-Ready Features

Tiger Data, the company behind TimescaleDB, has launched Agentic Postgres, a Postgres-based database designed for both AI agents and developers. It extends Postgres with fast forking, an MCP server, native BM25 and vector search, and includes a CLI for terminal access. By Sergio De Simone

Vector db comparison

I built a search engine that uses vector embeddings

deepseek-ai/DeepSeek-V3.2 · Hugging Face

deepseek-ai/DeepSeek-V3.2 · Hugging Face

AI is great, but only when it knows where to look

Is AI search changing how people find websites?

Optimizing filtered vector queries from tens of seconds to single-digit milliseconds in PostgreSQL

I worked on RAG for a $25B+ company (What I learnt & Challenges)

Optimizing filtered vector queries from tens of seconds to single-digit milliseconds in PostgreSQL

qdrant

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qdrant

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

chroma-core

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chroma

Open-source search and retrieval database for AI applications.

facebookresearch

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faiss

A library for efficient similarity search and clustering of dense vectors.

run-llama

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llama_index

LlamaIndex is the leading framework for building LLM-powered agents over your data.

pgvector

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pgvector

Open-source vector similarity search for Postgres

meilisearch

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meilisearch

A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.

weaviate

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weaviate

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

milvus-io

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milvus

Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

google

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highway

Performance-portable, length-agnostic SIMD with runtime dispatch