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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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Quantize Your Vectors, Speed Up Your Java AI Applications
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Quantize Your Vectors, Speed Up Your Java AI Applications

5
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20 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
How to Build Semantic Search in ASP.NET Core using PostgreSQL
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How to Build Semantic Search in ASP.NET Core using PostgreSQL

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

1
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4 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
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
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🚀 Sample RAG app with Strands, Reflex and S3

8
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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

1
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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
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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
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RAGs for Dummies: The Game-Changing Power of RAG

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3 min read
Vector Podcast: Simon Eskildsen, Turbopuffer
Cover image for Vector Podcast: Simon Eskildsen, Turbopuffer

Vector Podcast: Simon Eskildsen, Turbopuffer

10
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2 min read
Graph-Augmented Hybrid Retrieval and Multi-Stage Re-ranking: A Framework for High-Fidelity Chunk Retrieval in RAG Systems
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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

2
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10 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)
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Beyond Keywords: Optimizing Vector Search With Filters and Caching (Part 2)

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

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3 min read
Building with Generative AI: Lessons from 5 Projects Part 2: Embedding
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Building with Generative AI: Lessons from 5 Projects Part 2: Embedding

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9 min read
🧠 GenAI as a Backend Engineer: Part 2 - Vector DBs
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🧠 GenAI as a Backend Engineer: Part 2 - Vector DBs

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3 min read
Vector Database: Core Concepts
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Vector Database: Core Concepts

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4 min read
💡 What's new in txtai 9.0

💡 What's new in txtai 9.0

2
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5 min read
Snowflake AI_EMBED Function - Your Gateway to Unified Multimodal Vector Search

Snowflake AI_EMBED Function - Your Gateway to Unified Multimodal Vector Search

1
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5 min read
Sub-millisecond similarity search on IVF indexes with PDX
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Sub-millisecond similarity search on IVF indexes with PDX

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6 min read
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