With vector databases now powering business competitiveness through super-fast applications such as recommendation engines, it’s no surprise that the vector database market is set to grow 23% CAGR by 2032 (Markets and Markets).


Vector Search with Relational Databases using PostgreSQL
本课程是 Vector Database Fundamentals 专项课程 的一部分


位教师:SkillUp
包含在 中
您将学到什么
Describe the principles of modeling vector data in Relational databases (RDBMS).
Apply the commands necessary to store, retrieve, and query vectors efficiently in PostgreSQL.
Implement indexing techniques and optimization strategies for enhancing vector search performance.
Demonstrate, through hands-on labs, how to set up environments and perform vector searches using PostgreSQL.
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3 项作业
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该课程共有1个模块
Welcome to this module, where you’ll learn how to implement vector searches using relational databases. You’ll begin with a recap of RDBMS and then dive into the structures RDBMS uses to support vector data types and queries. You’ll apply what you know to perform similarity search tasks using special operators available in PostgreSQL. And, with a focus on PostgreSQL, you’ll learn how to create tsvector data, perform tsquery tasks, and perform bulk inserts using pg-vector for Node.js and psycopg2 for Python.
涵盖的内容
8个视频5篇阅读材料3个作业6个应用程序项目5个插件
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已于 Oct 22, 2024审阅
Such good and detailed course contents, very helpful.
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