Vector Search

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When More Cores Hurts: The Vector Database Scaling Paradox in HPC

 🔗RAG  Content type: Academic
arxiv.org·

Pinecone vs Qdrant vs Weaviate

 🔍Information Retrieval  Content type: Blog
rephrase-it.com·

aayush4vedi/drift-spark: Spark-native embedding lifecycle- produce, CDC refresh, model-migrate, audit.

 💻Technology Policy  Content type: Code
github.com··Hacker News

HNSW vs LSH: How Elasticsearch hits 0.99 recall@10 at 15,000 QPS — and what it costs

 🔍Information Retrieval  Content type: Blog
elastic.co·

A Fun & Absurd Introduction to Vector Databases • Alexander Chatzizacharias

 🔗RAG  Content type: Video
youtu.be··r/programming

Understanding HNSW: The Engine Behind Fast Vector Search

 🗂️Data Structures
chimchim89.github.io·

Quiz: Embeddings and Vector Databases With ChromaDB

 🔗RAG
realpython.com·

How to Build an Agentic RAG with RubyLLM and Rails

 🔗RAG  Content type: Blog
panasiti.me··Hacker News

MongoDB as a Vector Database for AI Agents-MongoDB

 🔗RAG
foojay.io·

Full Observability for Pinecone: Introducing an Open-Source Monitoring Stack for SaaS and BYOC

 🔍Information Retrieval  Content type: Blog
pinecone.io·

a desktop GUI to browse, search, & visualize your vector databases

 🔗RAG
vectorlens.dev··Hacker News

Building Semantic Search with Transformers.js and Sentence Embeddings

 💬Natural Language Processing

New comment by yorktanaka2024 in "Ask HN: Who wants to be hired? (June 2026)"

 🔗RAG  Content type: Discussion

Enterprises Are Quietly Moving Their AI Back On-Premises. Here Is Why.

 🔍Information Retrieval  Content type: Blog
medium.com·

How to Set Up Codebase Indexing in Kilo Code

 🤖Local LLMs  Content type: News  Content type: Blog
blog.kilo.ai·

HNSW-MS: Hierarchical Graph Indexing Enables Accurate Real-Time Mass Spectral Similarity Search at Repository Scale

 📊TF-IDF  Content type: Academic
biorxiv.org·

Introducing SQL Data Insights Pro

 🔍Information Retrieval  Content type: Blog
research.ibm.com·

New comment by jasonlayton4323 in "Ask HN: Who wants to be hired? (June 2026)"

 🔗RAG

cylburn

 🔍Information Retrieval
margarinalia.my·

Embedding pipelines are the new ETL

 ⚙️Data Engineering  Content type: Blog
infoworld.com·

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