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# vectordatabase

Vector databases are purpose-built databases that are specialized to tackle the problems that arise when managing vector embeddings in production scenarios.

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Teaching Security Scanners to Remember - Using Vector Embeddings to Stop Chasing Ghost Ports

Teaching Security Scanners to Remember - Using Vector Embeddings to Stop Chasing Ghost Ports

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4 min read
How to Build Semantic Search in ASP.NET Core using PostgreSQL

How to Build Semantic Search in ASP.NET Core using PostgreSQL

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3 min read
Caching in Vector Database: What You Need to Know

Caching in Vector Database: What You Need to Know

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4 min read
Building Your Notion AI with pgvector in 10 Minutes

Building Your Notion AI with pgvector in 10 Minutes

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6 min read
Why Privacy-First Databases Will Be the New Gold Standard

Why Privacy-First Databases Will Be the New Gold Standard

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3 min read
The Battle of Real-Time Databases: Firebase vs Supabase vs Postgres

The Battle of Real-Time Databases: Firebase vs Supabase vs Postgres

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3 min read
Graph-Augmented Hybrid Retrieval and Multi-Stage Re-ranking: A Framework for High-Fidelity Chunk Retrieval in RAG Systems

Graph-Augmented Hybrid Retrieval and Multi-Stage Re-ranking: A Framework for High-Fidelity Chunk Retrieval in RAG Systems

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33 min read
GraphRAG with Wikipedia and GPT OSS

GraphRAG with Wikipedia and GPT OSS

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10 min read
Quantize Your Vectors, Speed Up Your Java AI Applications

Quantize Your Vectors, Speed Up Your Java AI Applications

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20 min read
Embedded Intelligence: How SQLite-vec Delivers Fast, Local Vector Search for AI.

Embedded Intelligence: How SQLite-vec Delivers Fast, Local Vector Search for AI.

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7 min read
Building a 'Chat with Your Logs' System on AWS Using OpenSearch Serverless and Bedrock

Building a 'Chat with Your Logs' System on AWS Using OpenSearch Serverless and Bedrock

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7 min read
Furniture Image Classification Using TypeScript + BilberryDB SDK vs. No-Code Approach

Furniture Image Classification Using TypeScript + BilberryDB SDK vs. No-Code Approach

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4 min read
💡 What's new in txtai 9.0

💡 What's new in txtai 9.0

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5 min read
Day 7 — FAISS empty vectors, metric mismatch, and recall collapse (ProblemMap No.8)

Day 7 — FAISS empty vectors, metric mismatch, and recall collapse (ProblemMap No.8)

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3 min read
🚀 Sample RAG app with Strands, Reflex and S3

🚀 Sample RAG app with Strands, Reflex and S3

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2 min read
From Zero to 1 B Vectors: the 2025 No-BS Picking Guide

From Zero to 1 B Vectors: the 2025 No-BS Picking Guide

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2 min read
Semantic Embedding in RAG: why close vectors still miss meaning and how to fix it

Semantic Embedding in RAG: why close vectors still miss meaning and how to fix it

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4 min read
The low-cost path to AI Mastery: building a Wiki Navigator with pure Similarity Search

The low-cost path to AI Mastery: building a Wiki Navigator with pure Similarity Search

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7 min read
RAGs for Dummies: The Game-Changing Power of RAG

RAGs for Dummies: The Game-Changing Power of RAG

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3 min read
Vector Podcast: Simon Eskildsen, Turbopuffer

Vector Podcast: Simon Eskildsen, Turbopuffer

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2 min read
Unlocking the Potential of Vector Databases for AI Agents

Unlocking the Potential of Vector Databases for AI Agents

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4 min read
Beyond Keywords: Optimizing Vector Search With Filters and Caching (Part 2)

Beyond Keywords: Optimizing Vector Search With Filters and Caching (Part 2)

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8 min read
Moving Your Vector Database from ChromaDB to Milvus

Moving Your Vector Database from ChromaDB to Milvus

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10 min read
Crafting a Monster Hunter Wilds AI Assistant: Scrapy, Vector Search & Prompt Engineering

Crafting a Monster Hunter Wilds AI Assistant: Scrapy, Vector Search & Prompt Engineering

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8 min read
The Missing Link: How to Retrieve Full Documents with AWS S3 Vectors

The Missing Link: How to Retrieve Full Documents with AWS S3 Vectors

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3 min read
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