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The Rise of Vector and Graph Databases in Generative AI Implementations

Publisher IDC
Published Mar 29, 2024
Length 8 Pages
SKU # IDC18658423

Description

The Rise of Vector and Graph Databases in Generative AI Implementations


This IDC Perspective explores the development of multimodal capabilities through vector databases in generative AI (GenAI). It delves into constructing a GenAI ecosystem, ranging from establishing the data layer to highlighting the significance of vector and graph databases for GenAI development."As organizations discover value from GenAI, there is a move toward building bespoke solutions using these large language models (LLMs). Vector databases provide highly efficient storage mechanisms for multimodal enterprise data and augment search and recommendation capabilities from huge data sets. Vector databases are now an integral part of the GenAI data value chain," says Deepika Giri, associate VP, Data and AI, IDC Asia/Pacific.

Please Note: Extended description available upon request.

Table of Contents

8 Pages
Executive Snapshot
Situation Overview
Building a Robust Generative AI Ecosystem
Expanding the Data Layer for GenAI: The Need for Multimodal Capabilities
Build Versus Buy
The Rise of Vector Databases
Retrieval-Augmented Generation
RAG Architectures Explained
RAG Paradigms
Advanced RAG
Graph Databases for GenAI
Advice for the Technology Buyer
Learn More
Related Research
Synopsis

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