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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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Architectural Consolidation for Low-Latency Retrieval Systems: Why We Co-Located Transport, Embedding, Search, and Reranking

Architectural Consolidation for Low-Latency Retrieval Systems: Why We Co-Located Transport, Embedding, Search, and Reranking

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4 min read
I Built a Baseline RAG System — Then Measured Where It Actually Breaks

I Built a Baseline RAG System — Then Measured Where It Actually Breaks

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3 min read
I Built a Baseline RAG System — Then Measured Where It Actually Breaks

I Built a Baseline RAG System — Then Measured Where It Actually Breaks

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3 min read
The Cost-Based Revolution: Why Hybrid Search Optimization is the Missing Piece in Vector Databases

The Cost-Based Revolution: Why Hybrid Search Optimization is the Missing Piece in Vector Databases

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8 min read
SentinelSlice- Architecting Agentic Memory with Elastic Cloud and High-Density Vectors

SentinelSlice- Architecting Agentic Memory with Elastic Cloud and High-Density Vectors

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7 min read
PageIndex vs Vector RAG: Why Reasoning-Based Retrieval Achieves 98.7% Accuracy (Not 31%)

PageIndex vs Vector RAG: Why Reasoning-Based Retrieval Achieves 98.7% Accuracy (Not 31%)

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8 min read
Why Real-Time Analytics Can’t Depend on Cloud in 2026

Why Real-Time Analytics Can’t Depend on Cloud in 2026

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14 min read
Mini Tip of the Day - Preloading the License into the Docker IRIS Image

Mini Tip of the Day - Preloading the License into the Docker IRIS Image

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8 min read
Federation Over Embeddings: Let AI Agents Query Data Where It Lives

Federation Over Embeddings: Let AI Agents Query Data Where It Lives

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8 min read
Accelerating Multimodal Vector DB with Hugging Face + LanceDB

Accelerating Multimodal Vector DB with Hugging Face + LanceDB

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14 min read
Exploring Search Capabilities With Atlas Search-Part 2

Exploring Search Capabilities With Atlas Search-Part 2

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10 min read
From RAG to Agents: How TiDB Powers Modern AI Applications

From RAG to Agents: How TiDB Powers Modern AI Applications

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11 min read
From Data to Dialogue: Creating a Technical Design for Smart FAQs using LLMs, Pinecone & Kafka

From Data to Dialogue: Creating a Technical Design for Smart FAQs using LLMs, Pinecone & Kafka

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7 min read
Vector Databases Explained: Architecture and System Design for AI Apps

Vector Databases Explained: Architecture and System Design for AI Apps

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6 min read
From Documents to Answers: How RAG Works

From Documents to Answers: How RAG Works

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3 min read
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