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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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Introducing ShapedQL: The SQL Engine for Search, Feeds, and AI Agents
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Introducing ShapedQL: The SQL Engine for Search, Feeds, and AI Agents

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3 min read
From Web to Vector: Building RAG Pipelines
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From Web to Vector: Building RAG Pipelines

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6 min read
Oracle AI Vector Search in Oracle Database 23ai
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Oracle AI Vector Search in Oracle Database 23ai

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6 min read
How a RAG Agent Helped My Father's Shoulder Treatment (And Saved ₹30,000).
Cover image for How a RAG Agent Helped My Father's Shoulder Treatment (And Saved ₹30,000).

How a RAG Agent Helped My Father's Shoulder Treatment (And Saved ₹30,000).

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5 min read
Self-RAG vs Adaptive RAG vs Corrective RAG
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Self-RAG vs Adaptive RAG vs Corrective RAG

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3 min read
OpenCode as a txtai LLM

OpenCode as a txtai LLM

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3 min read
Why Feature Stores Didn't Fix Training–Serving Skew
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Why Feature Stores Didn't Fix Training–Serving Skew

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4 min read
The Two-Brain Architecture: Decoupling Recall from Learning

The Two-Brain Architecture: Decoupling Recall from Learning

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2 min read
Distilling Knowledge into Tiny LLMs

Distilling Knowledge into Tiny LLMs

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3 min read
Revolutionize Your Search with Snowflake Cortex Search Multi-Index and Index-Specific Boosts

Revolutionize Your Search with Snowflake Cortex Search Multi-Index and Index-Specific Boosts

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11 min read
RAG on AWS Just Got Simpler with S3 Vector
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RAG on AWS Just Got Simpler with S3 Vector

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5 min read
Local RAG vs Cloud RAG: What Changes When You Leave the Demo
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Local RAG vs Cloud RAG: What Changes When You Leave the Demo

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3 min read
Prompt Routing & Context Engineering: Letting the System Decide What It Needs
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Prompt Routing & Context Engineering: Letting the System Decide What It Needs

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3 min read
Building Enterprise Vector Search in Rails (Part 2/3): Production Resilience & Monitoring
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Building Enterprise Vector Search in Rails (Part 2/3): Production Resilience & Monitoring

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7 min read
Research Vault: Open Source Agentic AI Research Assistant
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Research Vault: Open Source Agentic AI Research Assistant

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5 min read
What Is a Vector Database? A Practical Deep Dive with Milvus

What Is a Vector Database? A Practical Deep Dive with Milvus

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1 min read
Building an AI-Powered Product Chat with Amazon S3 Vectors and Nova Lite

Building an AI-Powered Product Chat with Amazon S3 Vectors and Nova Lite

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2 min read
Your Vector Database is Not a Memory System

Your Vector Database is Not a Memory System

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2 min read
Automotive Software Explained: ECUs, ADAS, OTA Updates & Vehicle Connectivity

Automotive Software Explained: ECUs, ADAS, OTA Updates & Vehicle Connectivity

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3 min read
Why “Lost in the Middle” Breaks Most RAG Systems
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Why “Lost in the Middle” Breaks Most RAG Systems

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2 min read
Loaders, Splitters & Embeddings — How Bad Chunking Breaks Even Perfect RAG Systems

Loaders, Splitters & Embeddings — How Bad Chunking Breaks Even Perfect RAG Systems

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3 min read
Efficient Vector Storage for AI: Why I Chose Pinecone with AWS

Efficient Vector Storage for AI: Why I Chose Pinecone with AWS

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2 min read
Running AI on premises with Postgres
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Running AI on premises with Postgres

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7 min read
Vector-Database: Qdrant-cluster on ECS-Fargate

Vector-Database: Qdrant-cluster on ECS-Fargate

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4 min read
Dense vs Sparse Vector Stores: Which One Should You Use — and When?

Dense vs Sparse Vector Stores: Which One Should You Use — and When?

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2 min read
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