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  • Chromaとは？次世代AIを支えるベクトルデータベースの魅力と . . .
    オンラインショッピングサイトやデータベースの検索機能を強化したい場合に、Chromaが力を発揮します。商品検索では、単なるキーワード一致ではなく、商品の特徴やユーザーの意図を考慮した高度な検索が可能です。
  • Chroma
    Chroma is the open-source AI application database Batteries included Embeddings, vector search, document storage, full-text search, metadata filtering, and multi-modal All in one place Retrieval that just works As it should be
  • Vector DB Benchmark - Chroma vs Milvus vs PgVector vs Redis
    Benchmark the performance of Chroma, Milvus, PgVector, and Redis using VectorDBBench This article explores key metrics such as recall, queries per second (QPS), and latency across different HNSW parameter configurations The results highlight trade-offs in vector search performance
  • Chroma (vector database) - Wikipedia
    Chroma or ChromaDB is an open-source vector database tailored to applications with large language models [2] Its headquarters are in San Francisco In April 2023, it raised 18 million US dollars as seed funding [3]
  • GitHub - chroma-core chroma: the AI-native open-source . . .
    Embeddings databases (also known as vector databases) store embeddings and allow you to search by nearest neighbors rather than by substrings like a traditional database By default, Chroma uses Sentence Transformers to embed for you but you can also use OpenAI embeddings, Cohere (multilingual) embeddings, or your own
  • Choosing a Vector Database: Milvus vs. Chroma DB - Zilliz
    Chroma vector database is a noteworthy lightweight vector database, prioritizing ease of use and development-friendliness In contrast, Milvus, an AI native, open-source purpose-built vector database, excels in handling large-scale, high-performance, and low-latency applications
  • ベクター データベース: ChromaDB の概要など - HackerNoon
    ChromaDB offers various storage options, such as DuckDB for standalone use or ClickHouse for scalability It provides Python and JavaScript TypeScript SDKs and emphasizes simplicity, speed, and analysis capabilities ChromaDB can store vectors with additional metadata and allows for filtering during the query search on the vector database
  • Vespa vs Chroma: A Detailed Comparison in Vector . . .
    ChromaDB, an open-source vector database renowned for its scalability and robust support for machine learning endeavors, stands out with its user-friendly interface and adaptability to varying data complexities
  • ChromaDB: The Future Of Vector Databases In AI
    Chroma Vector Database (ChromaDB) is an open-source vector database designed specifically for managing and retrieving vector embeddings It plays a pivotal role in AI-driven tasks like semantic search, NLP, image recognition, and various machine learning applications
  • ChromaDB: The Lightweight Open-Source Vector Database for . . .
    ChromaDB is a vector database for storing and querying embeddings It provides an easy-to-use interface for AI developers to integrate similarity search into their applications Who is it for? Enable pgvector extension in PostgreSQL: client = chromadb PersistentClient(path="my_chroma_db")
  • Vector Database Comparison: Pinecone vs Weaviate vs . . .
    Compare Pinecone, Weaviate, and Chroma vector databases Performance benchmarks, pricing, and implementation guides to choose the right solution Choosing the right vector database can make or break your AI application’s performance
  • Chroma DB: The Ultimate Vector Database for AI and . . .
    Chroma DB is a modern, high-performance vector database designed specifically for machine learning applications It’s built to store and manage embeddings, which are vector representations of data, such as text, images, and other data types that are commonly used in AI models





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