当前位置:首页 > 报告详情

4142 - AI 搜索实战:将 Milvus 扩展到十亿级向量.pdf

上传人: 竿*** 编号:982860 2025-11-29 26页 1.10MB

1、1|Copyright 2025 Zilliz1Jiang Chen ZillizSession 4142AI Search in Action:Scaling Milvus for Billion-Scale Vectors2|Copyright 2025 Zilliz2 2|Copyright 9/6/23 Zilliz2|Copyright 2025 ZillizJiang ChenHead of Developer Rhttps:/ 2025 Zilliz3|Copyright 2025 Zilliz3Shift in Search and Data Paradigm4|Copyrig

2、ht 2025 Zilliz4Traditional database was built upon exact search5|Copyright 2025 Zilliz5AppleRising doughChange car tireRising DoughProofing Breadwhich misses context,semantic meaning,and user intent 6|Copyright 2025 Zilliz6*Data Source:The Digitization of the World by IDC10%Otherof newly generated d

3、ata in 2025 will be unstructured data90%The world is much more than just text and keywords7|Copyright 2025 Zilliz7 7|Copyright 2025 Zilliz7Vector search is the new standard8|Copyright 2025 Zilliz8A New tool emerged.The Vector Database9|Copyright 2025 Zilliz9 9|Copyright 9/6/23 Zilliz9|Copyright 2025

4、 ZillizRetrieval Augmented Generation(RAG)10|Copyright 2025 Zilliz1010|Copyright 9/6/23 Zilliz10|Copyright 2025 ZillizSearch/Recommendation System11|Copyright 2025 Zilliz1111|Copyright 9/6/23 Zilliz11|Copyright 2025 ZillizAgent MemoryMilvus as the central information repository for agentic workflow1

5、2|Copyright 2025 Zilliz1212|Copyright 9/6/23 Zilliz12|Copyright 2025 ZillizTwo Stages of AI Search DevelopmentThrive with great search qualityConsistently deliver the best performance at scale15|Copyright 2025 Zilliz15|Copyright 2025 Zilliz15Milvus is an Open-Source Vector Database to store,index,ma

6、nage,and use massive number of vector embeddings for information retrieval.contributors300+stars36K+active pods100M+forks3.3K+Milvus:The most widely-adopted vector database16|Copyright 2025 Zilliz1616|Copyright 9/6/23 Zilliz16|Copyright 2025 ZillizBUILT FOR AIOPEN SOURCEPerformant at ScaleWhy Milvus

word格式文档无特别注明外均可编辑修改,预览文件经过压缩,下载原文更清晰!
三个皮匠报告文库所有资源均是客户上传分享,仅供网友学习交流,未经上传用户书面授权,请勿作商用。
根据报告的内容,全文主要内容概括如下: - **搜索和数据范式转变**:传统数据库依赖精确搜索,而现代数据以非结构化为主,向量搜索成为新标准。 - **向量数据库兴起**:向量数据库如Milvus应运而生,用于存储、索引和管理大量向量嵌入,支持信息检索。 - **Milvus特点**:Milvus是一个开源向量数据库,支持亿级向量存储,性能卓越,完全开源。 - **Milvus发展历程**:从2.0到3.0版本,Milvus不断进化,引入了分层存储、RaBitQ量化方法等。 - **性能提升**:Milvus在动态字段测试中性能提升10-100倍。 - **应用场景**:Milvus适用于数据清洗、标签提取、数据挖掘和迭代搜索等场景。
"向量搜索新趋势是什么?" "如何实现亿级向量检索?" "Milvus 3.0有哪些新特性?"
客服
商务合作
小程序
服务号
折叠