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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 a smarter Web scraper: Vector embeddings for intelligent content retrieval

Building a smarter Web scraper: Vector embeddings for intelligent content retrieval

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3 min read
Recent Trends in Distributed Warehousing and Data Mining

Recent Trends in Distributed Warehousing and Data Mining

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2 min read
Meetup: Vector databases, RAG, BM25, sparse searches, AI model training

Meetup: Vector databases, RAG, BM25, sparse searches, AI model training

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2 min read
Vector Search in Action: Personalization with AI Embeddings

Vector Search in Action: Personalization with AI Embeddings

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5 min read
Why PostgreSQL Might Be All the Backend You Need: Forget the Kitchen Sink

Why PostgreSQL Might Be All the Backend You Need: Forget the Kitchen Sink

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4 min read
Beyond Basic Practice: Creating the JobSage AI Interview Simulator with Gemini & Embeddings

Beyond Basic Practice: Creating the JobSage AI Interview Simulator with Gemini & Embeddings

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5 min read
Entendiendo los Embeddings en Inteligencia Artificial

Entendiendo los Embeddings en Inteligencia Artificial

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3 min read
Smarter RAG Systems with Graphs

Smarter RAG Systems with Graphs

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4 min read
Postgres vs. Qdrant: Why Postgres Wins for AI and Vector Workloads

Postgres vs. Qdrant: Why Postgres Wins for AI and Vector Workloads

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4 min read
Vector Databases: their utility and functioning (RAG usage)

Vector Databases: their utility and functioning (RAG usage)

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12 min read
Improve Your Python Search Relevancy with Astra DB Hybrid Search

Improve Your Python Search Relevancy with Astra DB Hybrid Search

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11 min read
Build Code-RAGent, an agent for your codebase

Build Code-RAGent, an agent for your codebase

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5 min read
Semantic Search with Spring Boot & Redis

Semantic Search with Spring Boot & Redis

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10 min read
Setting up the Pinecone MCP server in your IDE

Setting up the Pinecone MCP server in your IDE

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3 min read
Ingest (almost) any non-PDF document in a vector database, effortlessly

Ingest (almost) any non-PDF document in a vector database, effortlessly

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3 min read
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