Report Content
Chapter 1 Methodology & Scope
1.1 Market scope & definition
1.2 Base estimates & calculations
1.3 Forecast calculation
1.4 Data sources
1.4.1 Primary
1.4.2 Secondary
1.4.2.1 Paid sources
1.4.2.2 Public sources
Chapter 2 Executive Summary
2.1 Vector database market 360º synopsis, 2018 - 2032
2.2 Business trends
2.2.1 Total Addressable Market (TAM), 2023-2032
2.3 Regional trends
2.4 Technology trends
2.5 Type trends
2.6 Industry vertical trends
Chapter 3 Vector Database Industry Insights
3.1 Impact of COVID-19
3.2 Industry ecosystem analysis
3.3 Vendor matrix
3.4 Profit margin analysis
3.5 Technology & innovation landscape
3.6 Patent analysis
3.7 Key news and initiatives
3.7.1 Partnership/Collaboration
3.7.2 Merger/Acquisition
3.7.3 Investment
3.7.4 Technology launch & innovation
3.8 Regulatory landscape
3.9 Impact forces
3.9.1 Growth drivers
3.9.1.1 Growing data volume and complexity
3.9.1.2 Rising adoption of Artificial Intelligence (AI) and Machine Learning (ML) across industries
3.9.1.3 Increasing need for real-time analytics
3.9.1.4 Rising demand for geospatial and time-series data analysis
3.9.2 Industry pitfalls & challenges
3.9.2.1 High cost of commercial vector databases
3.9.2.2 Complex setup and management
3.10 Growth potential analysis
3.11 Porter’s analysis
3.12 PESTEL analysis
Chapter 4 Competitive Landscape, 2022
4.1 Introduction
4.2 Company market share, 2022
4.3 Competitive analysis of major market players, 2022
4.3.1 Pinecone
4.3.2 MongoDB
4.3.3 Milvus
4.3.4 Qdrant
4.3.5 KX
4.3.6 Zilliz
4.3.7 DataStax
4.4 Competitive positioning matrix, 2022
4.5 Strategic outlook matrix, 2022
Chapter 5 Vector Database Market Estimates & Forecast, By Technology (Revenue)
5.1 Key trends, by technology
5.2 Natural language processing
5.3 Computer Vision
5.4 Recommendation Systems
Chapter 6 Vector Database Market Estimates & Forecast, By Type (Revenue)
6.1 Key trends, by type
6.2 Services
6.2.1 Vector Generation
6.2.2 Vector Search
6.2.3 Storage and Retrieval Vectors
6.3 Solution
6.3.1 Professional Services
6.3.2 Managed Services
Chapter 7 Vector Database Market Estimates & Forecast, By Industry vertical (Revenue)
7.1 Key trends, by industry vertical
7.2 Retail & E-Commerce
7.3 BFSI
7.4 Retail
7.5 Media & Entertainment
7.6 Healthcare & Life Sciences
7.7 Manufacturing
7.8 IT & Telecom
7.9 Others
Chapter 8 Vector Database Market Estimates & Forecast, By Region (Revenue)
8.1 Key trends, by region
8.2 North America
8.2.1 U.S.
8.2.2 Canada
8.3 Europe
8.3.1 UK
8.3.2 Germany
8.3.3 France
8.3.4 Italy
8.3.5 Spain
8.3.6 Nordics
8.4 Asia Pacific
8.4.1 China
8.4.2 India
8.4.3 Japan
8.4.4 Australia
8.4.5 South Korea
8.4.6 Southeast Asia
8.5 Latin America
8.5.1 Brazil
8.5.2 Mexico
8.5.3 Argentina
8.6 MEA
8.6.1 UAE
8.6.2 Saudi Arabia
8.6.3 South Africa
Chapter 9 Company Profiles
9.1 Chroma DB
9.2 DataStax
9.3 Elastic
9.4 KX
9.5 Marqo AI
9.6 Microsoft
9.7 Milvus
9.8 MongoDB
9.9 MyScale
9.10 OpenSearch
9.11 Pinecone
9.12 Qdrant
9.13 Redis
9.14 Rockset
9.15 SingleStore
9.16 Supabase
9.17 Typesense
9.18 Vespa
9.19 Weaviate
9.20 Zilliz
