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Redis + AI: Building a Vector Database with Redis

2h 32mIntermediate2024-07-31

Authors

Fernando Doglio

Published Author, Developer Advocate at OpenReplay

Course details

This course shows developers how to exploit the ready-made AI-related tools in Redis to build a vector database. Instructor Fernando Doglio starts with a look at structured versus unstructured data and AI-optimized databases, then jumps into Redis Enterprise to talk about how developers can use it as a vector DB. He also showcases examples like recommendation engines, semantic search, and others.

Skills covered

RedisMachine LearningDatabase DevelopmentArtificial Intelligence FoundationsDatabase ManagementArtificial Intelligence (AI)Open SourceSoftware DevelopmentOne-Off

Concepts

0. Introduction

01 - Introduction
02 - What you should know

1. Understanding Data

03 - What is structured data and where does it come from
04 - What is unstructured data and where does it come from
05 - Using structured data
06 - Using unstructured data - Use case examples
07 - Which is better Structured vs. unstructured data
08 - Unstructured to structured data
09 - Practical example - Metadata

2. AI-Optimized Databases

10 - What are AI-optimized databases
11 - What are vector databases
12 - What are embeddings
13 - How do vector databases work
14 - Examples of use cases for vector databases

3. Enter Redis

15 - Quick introduction of RediSearch and how to get it
16 - Redis used as a vector database
17 - Using Redis as a recommendation engine - Architecture overview
18 - Using Redis as a documentation retrieval database - Architecture review

4. Building an Image Similarity Search

19 - Introduction to the project to solve
20 - Architecture review - Using Redis as a vector database
21 - Tech stack overview
22 - Implementation overview - A deep dive into the main aspects of the implementation