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pgvector

19 articles · Page 1 of 1
Linyb Geek Road
Linyb Geek Road
Oct 1, 2026 · Artificial Intelligence

MaxKB: Open-Source RAG Knowledge Base with Model-Neutral Design & Zero-Code Embedding

MaxKB is an open-source AI knowledge base Q&A system from Fit2Cloud that uses RAG with pgvector and LangChain to provide model-neutral, out-of-the-box intelligent question answering, supporting Docker deployment, multi-format documents, visual workflows, and zero-code embedding via iframe or API for enterprise knowledge bases, customer service, and developer portals.

LLMLangChainMaxKB
0 likes · 18 min read
MaxKB: Open-Source RAG Knowledge Base with Model-Neutral Design & Zero-Code Embedding
MaGe Linux Operations
MaGe Linux Operations
Sep 26, 2026 · Operations

RAG System Operations: Vector Database Selection & Performance Tuning

This comprehensive guide covers end-to-end RAG system operations, from vector database selection and workload profiling to HNSW parameter tuning, filtering strategies, index freshness monitoring, embedding upgrades, capacity planning, backup validation, and troubleshooting methodologies with concrete examples and evaluation frameworks.

HNSWMilvusQdrant
0 likes · 64 min read
RAG System Operations: Vector Database Selection & Performance Tuning
Cloud Architecture
Cloud Architecture
Sep 12, 2026 · Backend Development

From Monolith to Distributed: Spring AI Embedding Product Semantic Recall System

This article details the evolution of a product semantic recall system using Spring AI Embedding, covering architecture design, reliable vector indexing with Outbox pattern, hybrid search fusion, pgvector HNSW tuning, and safe migration to Milvus, with production readiness criteria and observability practices.

MilvusOutbox PatternSpring AI
0 likes · 20 min read
From Monolith to Distributed: Spring AI Embedding Product Semantic Recall System
DataFunSummit
DataFunSummit
Jul 26, 2026 · Databases

Why Is PostgreSQL Gaining New Momentum as an AI‑Era Data Foundation?

PostgreSQL is attracting renewed interest not because it magically becomes an all‑purpose AI database, but because AI applications in production demand a unified, consistent platform that can manage business records, vector embeddings, agent state, permissions and tooling, and PostgreSQL’s extensible ecosystem—pgvector, serverless architectures, branching, and MCP—offers exactly that blend of relational reliability and AI‑native capabilities.

AIDatabase BranchingMCP
0 likes · 15 min read
Why Is PostgreSQL Gaining New Momentum as an AI‑Era Data Foundation?
AI Illustrated Series
AI Illustrated Series
Jul 13, 2026 · Artificial Intelligence

Building Enterprise‑Grade AI Agents in Java in 3 Days

This article walks Java developers through turning Spring AI into an enterprise‑grade AI agent that can query internal databases, access a vector‑based knowledge base, enforce role‑based permissions, persist chat sessions in Redis, add full observability, and be container‑deployed with Docker and Kubernetes.

AI agentJavaRedis
0 likes · 10 min read
Building Enterprise‑Grade AI Agents in Java in 3 Days
DeepHub IMBA
DeepHub IMBA
May 18, 2026 · Artificial Intelligence

Self‑Improving Multi‑Agent RAG System: Architecture, Evaluation, and Human‑Reviewed Prompt Loop

An end‑to‑end multi‑agent Retrieval‑Augmented Generation platform is presented, featuring compositional reasoning, systematic multi‑dimensional evaluation, and a controlled prompt‑improvement loop that automatically identifies weak prompt dimensions, proposes diffs, and requires human approval before deployment, with full observability via SSE and persisted logs.

FastAPIMulti-agentRAG
0 likes · 19 min read
Self‑Improving Multi‑Agent RAG System: Architecture, Evaluation, and Human‑Reviewed Prompt Loop
ITPUB
ITPUB
May 13, 2026 · Databases

Is the Hype Around Vector Databases a Pseudo‑Demand in the AI Era?

The article questions whether dedicated vector databases are truly needed for AI applications, examining market hype, the rapid emergence of many vector‑DB products, real‑world examples like PostgreSQL pgvector and major vendor integrations, and the hidden costs of data fragmentation and operational complexity.

AIPostgreSQLRAG
0 likes · 15 min read
Is the Hype Around Vector Databases a Pseudo‑Demand in the AI Era?
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Apr 22, 2026 · Databases

Unlock PostgreSQL’s Multi‑Model Power: Graph, Vector, Full‑Text, JSONB & GIS in Practice

PostgreSQL’s extensible architecture lets it evolve from a relational DB into a true multi‑model system supporting graphs, vectors, full‑text, time‑series, GIS and key‑value data, with detailed architecture explanations, practical code demos, cross‑model queries, extension selection, and production‑grade best‑practice tips.

Apache AGEJSONBPostGIS
0 likes · 39 min read
Unlock PostgreSQL’s Multi‑Model Power: Graph, Vector, Full‑Text, JSONB & GIS in Practice
AI Engineering
AI Engineering
Apr 11, 2026 · Artificial Intelligence

GBrain: Open-Source AI Memory Engine that Gives OpenClaw and Hermes Long-Term Recall

GBrain, an open‑source AI memory hub created by YC partner Garry Tan, combines Postgres tsvector keyword search with pgvector semantic search via RRF, manages thousands of Markdown notes, and runs an automated nightly agent that refines and links memories, offering a practical long‑term recall layer for agents like OpenClaw and Hermes.

AI memoryGBrainHermes
0 likes · 4 min read
GBrain: Open-Source AI Memory Engine that Gives OpenClaw and Hermes Long-Term Recall
Ray's Galactic Tech
Ray's Galactic Tech
Mar 30, 2026 · Artificial Intelligence

From Demo to Production: Building an Enterprise‑Grade RAG System with Spring AI & PGVector

This comprehensive guide explains how to design, implement, and operate a production‑ready Retrieval‑Augmented Generation (RAG) platform using Spring AI and PostgreSQL PGVector, covering architecture, indexing, hybrid retrieval, prompt engineering, scaling, security, observability, deployment, and common pitfalls for enterprise knowledge‑base applications.

Enterprise AIRAGSpring AI
0 likes · 42 min read
From Demo to Production: Building an Enterprise‑Grade RAG System with Spring AI & PGVector
Data STUDIO
Data STUDIO
Dec 23, 2025 · Databases

Is the Vector Database Dead? PostgreSQL’s New pgvector Feature Puts Closed‑Source Solutions on the Spot

The article examines how PostgreSQL’s latest pgvector 0.8.0 release adds iterative index scans and smart query planning, enabling fully free vector search within an existing relational database, compares performance, cost, and architecture against dedicated vector databases like Pinecone, and outlines migration steps and best‑practice guidelines.

AIBenchmarkPostgreSQL
0 likes · 14 min read
Is the Vector Database Dead? PostgreSQL’s New pgvector Feature Puts Closed‑Source Solutions on the Spot
ITPUB
ITPUB
Nov 15, 2024 · Databases

Why Vector Databases Matter: Deploying PgVector on PostgreSQL for Scalable AI Retrieval

This article explains the need for vector databases in the AI era, reviews PostgreSQL's extensible ecosystem, compares vector‑database options, provides step‑by‑step PgVector installation and usage, shares operational best practices, performance tuning tips, and real‑world Qunar & Tujia case studies.

AIPostgreSQLRAG
0 likes · 27 min read
Why Vector Databases Matter: Deploying PgVector on PostgreSQL for Scalable AI Retrieval