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Vector Databases
🗄️ Vector Databases
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embeddings, vector store, Pinecone, Weaviate, pgvector
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123
posts in
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ms
cylburn
🔍
RAG
margarinalia.my
·
3d
3 days ago
Actions for cylburn
You Probably Don’t Need a
Vector
Database
- If Your Data Already Lives in BigQuery
🔍
RAG
Content type:
Blog
medium.com
·
20h
20 hours ago
Actions for You Probably Don’t Need a Vector Database - If Your Data Already Lives in BigQuery
Redis vs Memorystore: key differences in 2026
💾
Agent Memory
Content type:
Blog
redis.io
·
1d
1 day ago
Actions for Redis vs Memorystore: key differences in 2026
Your AI agent reads the fine print: building a RAG pipeline over EU regulations with Elasticsearch and OGX
🔍
RAG
Content type:
Blog
elastic.co
·
3d
3 days ago
Actions for Your AI agent reads the fine print: building a RAG pipeline over EU regulations with Elasticsearch and OGX
Child Punctures Magritte Painting With
Pinecone
at Israel Museum
🔍
RAG
hyperallergic.com
·
2d
2 days ago
Actions for Child Punctures Magritte Painting With Pinecone at Israel Museum
Full Observability for
Pinecone
: Introducing an Open-Source Monitoring Stack for SaaS and BYOC
🔍
RAG
Content type:
Blog
pinecone.io
·
3d
3 days ago
Actions for Full Observability for Pinecone: Introducing an Open-Source Monitoring Stack for SaaS and BYOC
Child damages Magritte painting with
pinecone
🔍
RAG
Content type:
News
theartnewspaper.com
·
1d
1 day ago
Actions for Child damages Magritte painting with pinecone
Hashtag Jakarta EE #336
🔍
RAG
agilejava.eu
·
5d
5 days ago
Actions for Hashtag Jakarta EE #336
gharibyan/agent-memory: TypeScript SDK for building AI agents with automatic, scoped, persistent memory. `agent-memory` wraps model calls with memory recall and learning so apps can keep useful user, thread, and operation context without manually stuffing long chat histories into every prompt.
💾
Agent Memory
Content type:
Code
github.com
·
22h
22 hours ago
·
Hacker News
Actions for gharibyan/agent-memory: TypeScript SDK for building AI agents with automatic, scoped, persistent memory. `agent-memory` wraps model calls with memory recall and learning so apps can keep useful user, thread, and operation context without manually stuffing long chat histories into every prompt.
How to Build an Agentic RAG with RubyLLM and Rails
🔍
RAG
Content type:
Blog
panasiti.me
·
2d
2 days ago
·
Hacker News
Actions for How to Build an Agentic RAG with RubyLLM and Rails
Enterprises Are Quietly Moving Their AI Back On-Premises. Here Is Why.
🔍
RAG
Content type:
Blog
medium.com
·
4d
4 days ago
Actions for Enterprises Are Quietly Moving Their AI Back On-Premises. Here Is Why.
New comment by yorktanaka2024 in "Ask HN: Who wants to be hired? (June 2026)"
🔍
RAG
Content type:
Discussion
news.ycombinator.com
·
2d
2 days ago
·
Hacker News
Actions for New comment by yorktanaka2024 in "Ask HN: Who wants to be hired? (June 2026)"
Designing Memory for a Minimal Rust Coding Agent, Without a
Vector
Store
💾
Agent Memory
xavierforge.dev
·
6d
6 days ago
·
Hacker News
Actions for Designing Memory for a Minimal Rust Coding Agent, Without a Vector Store
The Read Model Zoo: Projections Beyond Tables - EventSourcingDB
🔍
RAG
Content type:
Blog
Content type:
Reference
docs.eventsourcingdb.io
·
4d
4 days ago
·
Hacker News
Actions for The Read Model Zoo: Projections Beyond Tables - EventSourcingDB
Knowledge Graphs for AI Coding Assistants
📐
Context Engineering
graphify.net
·
2d
2 days ago
Actions for Knowledge Graphs for AI Coding Assistants
Best practices for building a modern app with
vector
search
🔍
RAG
Content type:
Blog
elastic.co
·
4d
4 days ago
Actions for Best practices for building a modern app with vector search
I kept losing good answers in my AI chat history, so I built
search
for it
📐
Context Engineering
Content type:
Blog
indiehackers.com
·
4d
4 days ago
Actions for I kept losing good answers in my AI chat history, so I built search for it
LangChain vs LlamaIndex 2026: Response Time on 10 RAG Tasks
🧩
AI Frameworks
Content type:
Blog
Content type:
Discussion
tildalice.io
·
2d
2 days ago
Actions for LangChain vs LlamaIndex 2026: Response Time on 10 RAG Tasks
Cloudian closes gap between enterprise AI ambitions and messy production deployments
🔍
RAG
Content type:
News
blocksandfiles.com
·
3d
3 days ago
Actions for Cloudian closes gap between enterprise AI ambitions and messy production deployments
I Processed 2.4 Billion Tokens Across 52 AI Models for $0.52. Here's the Full Breakdown.
🎼
Agent Orchestration
saintlex.sbs
·
1d
1 day ago
·
DEV
Actions for I Processed 2.4 Billion Tokens Across 52 AI Models for $0.52. Here's the Full Breakdown.
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