AI 혁신에 권한 부여 : 벡터·테크놀러지의 역할

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."

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
• Synopsis