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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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Building an AI-Powered Semantic Talent Matching System

Building an AI-Powered Semantic Talent Matching System

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5 min read
The Database Zoo: Vector Databases and High-Dimensional Search

The Database Zoo: Vector Databases and High-Dimensional Search

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16 min read
Launching your RAG system on AWS: CloudFront, Lambda, Bedrock & S3 Vectors

Launching your RAG system on AWS: CloudFront, Lambda, Bedrock & S3 Vectors

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10 min read
Memory in AI Companions: Implementing Vector-Based Long-Term User State

Memory in AI Companions: Implementing Vector-Based Long-Term User State

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3 min read
MyScaleDB: Why Vector Databases Need SQL (The 2025 Reality Check)

MyScaleDB: Why Vector Databases Need SQL (The 2025 Reality Check)

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10 min read
Embeddings y RAG en aplicaciones web

Embeddings y RAG en aplicaciones web

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8 min read
You may not need pg_vector, sqlite-vss, etc.

You may not need pg_vector, sqlite-vss, etc.

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2 min read
Why Multi-Validator Hosts Break Traditional Security Scanning

Why Multi-Validator Hosts Break Traditional Security Scanning

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4 min read
How Google Mistook My Sui Node for a Bitcoin Farm (And Banned Me) (again)

How Google Mistook My Sui Node for a Bitcoin Farm (And Banned Me) (again)

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3 min read
Keyword vs. semantic search with AI

Keyword vs. semantic search with AI

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4 min read
Amazon S3 Vectors: When Storage Learns to Think

Amazon S3 Vectors: When Storage Learns to Think

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8 min read
Why Your RAG System Hallucinations Start at Ingestion, Not the LLM

Why Your RAG System Hallucinations Start at Ingestion, Not the LLM

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3 min read
Building a Vector Database from Scratch - CapybaraDB

Building a Vector Database from Scratch - CapybaraDB

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11 min read
Building a FHIR Vector Repository with InterSystems IRIS and Python through the IRIStool module

Building a FHIR Vector Repository with InterSystems IRIS and Python through the IRIStool module

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5 min read
Amazon S3 Vectors: The Cost-Friendly Way to Store and Search AI Embeddings

Amazon S3 Vectors: The Cost-Friendly Way to Store and Search AI Embeddings

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3 min read
🎓 Building a Smart LMS Assistant: RAG System with Pinecone for Multi-Source Learning Data

🎓 Building a Smart LMS Assistant: RAG System with Pinecone for Multi-Source Learning Data

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3 min read
An Introduction to LangChain

An Introduction to LangChain

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31 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
Accessing Low Level Vector APIs

Accessing Low Level Vector APIs

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7 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
Couchbase Weekly Updates - October 17, 2025

Couchbase Weekly Updates - October 17, 2025

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2 min read
MongoDB Vector Search With EF Core

MongoDB Vector Search With EF Core

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12 min read
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