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Empowering AI Innovation: The Role of Vector Technologies

Publisher IDC
Published Apr 09, 2025
Length 18 Pages
SKU # IDC19954084

Description

This IDC Market Perspective discusses how vector databases are transforming AI by enabling applications like semantic search, recommendation systems, and fraud detection. This document explores two key approaches: native vector databases, purpose-built for large-scale AI workloads, and integrated vector databases, which extend traditional platforms to support hybrid use cases. Organizations will gain insights into enhancing scalability, cost efficiency, and performance, while technology suppliers can uncover opportunities to optimize offerings for the growing AI market. Whether you’re driving innovation or seeking competitive advantages, this document is essential for understanding the future of AI-driven data management.“Vector databases are redefining the AI landscape by empowering organizations to harness high-dimensional data for transformative applications like generative AI, semantic search, and personalized recommendations,” says Devin Pratt, research director, Data Management, IDC. “As AI adoption accelerates, the decision between native vector databases and integrated vector databases will depend on specific organizational needs rather than purely technological factors. Both approaches are set to play vital and complementary roles in driving the next wave of AI-driven innovation.”

Table of Contents

18 Pages

Executive Snapshot

New Market Developments and Dynamics

Introduction

Understanding Vector Embeddings and Vector Stores

Vector Embeddings

Vectorization Process

Vector Stores

Applications of Vector Databases in AI

Key Applications

Native Vector Databases and Integrated Vector Databases

Native Vector Databases

Key Features of Native Vector Databases

Examples of Native Vector Databases

Pinecone

Milvus

Weaviate

Google Vertex AI Vector Search

Integrated Vector Databases

Key Features of Integrated Vector Databases

Examples of Integrated Vector Databases

PostgreSQL + pgvector

Azure SQL Database

IBM watsonx.data

Comparison Between Native and Integrated Vector Databases

Similarities

Differences

IDC’s Point of View

Native Versus Integrated Vector Databases

Native Vector Databases

Integrated Vector Databases

Hybrid Approaches

Future Outlook

Recommendations for Technology Suppliers

Enhance Performance Optimization

Recommendations

Enhance Multimodal Data Support

Recommendations

Prioritize Scalability and Performance Optimization

Recommendations

Focus on Seamless Integration and Compatibility

Recommendations

Learn More

Related Research

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