NeuronDB a PostgreSQL AI Extension
PostgreSQL extension for vector search, ML inference, and RAG. Includes HNSW indexing, GPU acceleration, 10 distance metrics, and pgvector compatibility.
Tutorials, guides, and technical insights about NeuronDB. Learn vector search, ML inference, RAG pipelines, and PostgreSQL AI extensions.
Tutorials and technical notes.
PostgreSQL extension for vector search, ML inference, and RAG. Includes HNSW indexing, GPU acceleration, 10 distance metrics, and pgvector compatibility.
Semantic search over text using NeuronDB. Includes examples, SQL queries, and code. Guide to building document search systems, RAG pipelines, and hybrid search.
Vector operations, indexing, and similarity search in PostgreSQL with NeuronDB. Guide with SQL queries and results. Covers HNSW indexing, distance metrics, quantization, and performance optimization.
MCP Server (Model Context Protocol) guide. What it is, how it works, integration with Claude Desktop, known MCP servers, and NeuronMCP implementation. How MCP enables AI assistants to access external tools and resources.
RAG (Retrieval-Augmented Generation) guide with examples, SQL queries, and implementation patterns. How to build RAG systems with document retrieval, context building, LLM integration, and response generation.
Core RAG architecture patterns: basic, conversational, filtered, adaptive, hypothesis-driven, agent-driven, and graph-based RAG. When to use each and what trade-offs matter in production.
Agentic AI systems guide. Agent architecture, planning, tool use, memory systems, and autonomous task execution. Implementation using NeuronDB and NeuronAgent with code examples.
Using PostgreSQL as a vector database. How PostgreSQL with NeuronDB extension works as a vector database with HNSW indexing, similarity search, and production capabilities.
Deploying AI workloads with databases on-premises. On-premises AI infrastructure, data sovereignty, security, performance, and implementation with NeuronDB. Architecture patterns, deployment strategies, and examples.
Complete guide to implementing Human-in-the-Loop (HITL) workflows and approval systems with NeuronAgent. Learn workflow engine architecture, approval state machines, and real-world implementation patterns.
Complete guide to implementing agent memory systems. Learn the differences between long-term and short-term memory, retrieval strategies, and implementation patterns with NeuronDB and NeuronAgent.
Step-by-step guide to integrating Claude Desktop with NeuronDB using NeuronMCP. Learn installation, configuration, testing, and common workflows for using NeuronDB tools in Claude Desktop.
Complete comparison of NeuronDB and pgvector features, performance benchmarks, and step-by-step migration guide. Learn when to use each solution and how to migrate from pgvector to NeuronDB.