Large-Scale Vector Indexing System - Global Top Players Market Share and Ranking 2025- YH Research

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Large-Scale Vector Indexing System - Global Top Players Market Share and Ranking 2025

Publication Date: 2025-11-04
Report Id: 2678503
Industry: Service & Software
Report Page: 99
Chart: 93

PDF Download

Publication Date: 2025-11-04
Report Id: 2678503
Industry: Service & Software
Report Page: 99
Chart: 93

PDF Download

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Table of Contents
Description
Table of Figures
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1 Market Overview
1.1 Large-Scale Vector Indexing System Definition
1.2 Global Large-Scale Vector Indexing System Market Size and Forecast
1.3 China Large-Scale Vector Indexing System Market Size and Forecast
1.4 Share of China Large-Scale Vector Indexing System Market with Respect to the Global Market
1.5 Large-Scale Vector Indexing System Market Size: China VS Global Growth Rate, 2020-2031
1.6 Large-Scale Vector Indexing System Market Dynamics
1.6.1 Large-Scale Vector Indexing System Market Drivers
1.6.2 Large-Scale Vector Indexing System Market Restraints
1.6.3 Large-Scale Vector Indexing System Industry Trends
1.6.4 Large-Scale Vector Indexing System Industry Policy

2 Global Leading Players and Market Share
2.1 By Revenue of Large-Scale Vector Indexing System, Global Market Share by Company, 2020-2025
2.2 Global Large-Scale Vector Indexing System Participants, Market Position (Tier 1, Tier 2, and Tier 3)
2.3 Global Large-Scale Vector Indexing System Concentration Ratio
2.4 Global Large-Scale Vector Indexing System Mergers & Acquisitions, Expansion Plans
2.5 Global Large-Scale Vector Indexing System Major Companies Product Type
2.6 Head Office and Area Served of Key Players

3 China Leading Players, Market Share and Ranking
3.1 By Revenue of Large-Scale Vector Indexing System, China Market Share by Company, 2020-2025
3.2 China Large-Scale Vector Indexing System Large-Scale Vector Indexing System Participants, Market Position (Tier 1, Tier 2, and Tier 3)

4 Industry Chain Analysis
4.1 Large-Scale Vector Indexing System Industry Chain
4.2 Large-Scale Vector Indexing System Upstream Analysis
4.2.1 Large-Scale Vector Indexing System Core Raw Materials
4.2.2 Main Manufacturers of Large-Scale Vector Indexing System Core Raw Materials
4.3 Midstream Analysis
4.4 Downstream Analysis
4.5 Large-Scale Vector Indexing System Production Mode
4.6 Large-Scale Vector Indexing System Procurement Model
4.7 Large-Scale Vector Indexing System Industry Sales Model and Sales Channels
4.7.1 Large-Scale Vector Indexing System Sales Model
4.7.2 Large-Scale Vector Indexing System Typical Distributors

5 Sights by Type
5.1 Large-Scale Vector Indexing System Classification by Type
5.1.1 Cloud-Based
5.1.2 Local Deployment
5.2 by Type, Global Large-Scale Vector Indexing System Consumption Value & CAGR, 2020 VS 2024 VS 2031
5.3 by Type, Global Large-Scale Vector Indexing System Consumption Value, 2020-2031

6 Sights by Storage Architecture
6.1 Large-Scale Vector Indexing System Classification by Storage Architecture
6.1.1 Centralized Vector Search
6.1.2 Distributed Vector Search
6.1.3 Others
6.2 by Storage Architecture, Global Large-Scale Vector Indexing System Consumption Value & CAGR, 2020 VS 2024 VS 2031
6.3 by Storage Architecture, Global Large-Scale Vector Indexing System Consumption Value, 2020-2031

7 Sights by Indexing Algorithm Type
7.1 Large-Scale Vector Indexing System Classification by Indexing Algorithm Type
7.1.1 Exact Search
7.1.2 Approximate Nearest Neighbor
7.2 by Indexing Algorithm Type, Global Large-Scale Vector Indexing System Consumption Value & CAGR, 2020 VS 2024 VS 2031
7.3 by Indexing Algorithm Type, Global Large-Scale Vector Indexing System Consumption Value, 2020-2031

8 Sights by Application
8.1 Large-Scale Vector Indexing System Segment by Application
8.1.1 Enterprise
8.1.2 Individual
8.2 by Application, Global Large-Scale Vector Indexing System Consumption Value & CAGR, 2020 VS 2024 VS 2031
8.3 by Application, Global Large-Scale Vector Indexing System Consumption Value, 2020-2031

9 Sales Sights by Region
9.1 By Region, Global Large-Scale Vector Indexing System Consumption Value, 2020 VS 2024 VS 2031
9.2 By Region, Global Large-Scale Vector Indexing System Consumption Value, 2020-2031
9.3 North America
9.3.1 North America Large-Scale Vector Indexing System Market Size & Forecasts, 2020-2031
9.3.2 By Country, North America Large-Scale Vector Indexing System Market Size Market Share
9.4 Europe
9.4.1 Europe Large-Scale Vector Indexing System Market Size & Forecasts, 2020-2031
9.4.2 By Country, Europe Large-Scale Vector Indexing System Market Size Market Share
9.5 Asia Pacific
9.5.1 Asia Pacific Large-Scale Vector Indexing System Market Size & Forecasts, 2020-2031
9.5.2 By Country/Region, Asia Pacific Large-Scale Vector Indexing System Market Size Market Share
9.6 South America
9.6.1 South AmericaLarge-Scale Vector Indexing System Market Size & Forecasts, 2020-2031
9.6.2 By Country, South America Large-Scale Vector Indexing System Market Size Market Share
9.7 Middle East & Africa

10 Sales Sights by Country Level
10.1 By Country, Global Large-Scale Vector Indexing System Market Size & CAGR, 2020 VS 2024 VS 2031
10.2 By Country, Global Large-Scale Vector Indexing System Consumption Value, 2020-2031
10.3 United States
10.3.1 United States Large-Scale Vector Indexing System Market Size, 2020-2031
10.3.2 by Type, United States Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.3.3 by Application, United States Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.4 Europe
10.4.1 Europe Large-Scale Vector Indexing System Market Size, 2020-2031
10.4.2 by Type, Europe Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.4.3 by Application, Europe Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.5 China
10.5.1 China Large-Scale Vector Indexing System Market Size, 2020-2031
10.5.2 by Type, China Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.5.3 by Application, China Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.6 Japan
10.6.1 Japan Large-Scale Vector Indexing System Market Size, 2020-2031
10.6.2 by Type, Japan Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.6.3 by Application, Japan Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.7 South Korea
10.7.1 South Korea Large-Scale Vector Indexing System Market Size, 2020-2031
10.7.2 by Type, South Korea Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.7.3 by Application, South Korea Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.8 Southeast Asia
10.8.1 Southeast Asia Large-Scale Vector Indexing System Market Size, 2020-2031
10.8.2 by Type, Southeast Asia Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.8.3 by Application, Southeast Asia Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.9 India
10.9.1 India Large-Scale Vector Indexing System Market Size, 2020-2031
10.9.2 by Type, India Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.9.3 by Application, India Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.10 Middle East & Africa
10.10.1 Middle East & Africa Large-Scale Vector Indexing System Market Size, 2020-2031
10.10.2 by Type, Middle East & Africa Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031
10.10.3 by Application, Middle East & Africa Large-Scale Vector Indexing System Consumption Value Market Share, 2024 VS 2031

11 Company Profile
11.1 Pinecone
11.1.1 Pinecone Company Information, Head Office, Market Area, and Industry Position
11.1.2 Pinecone Company Profile and Main Business
11.1.3 Pinecone Large-Scale Vector Indexing System Models, Specifications, and Application
11.1.4 Pinecone Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.1.5 Pinecone Recent Developments
11.2 Vespa
11.2.1 Vespa Company Information, Head Office, Market Area, and Industry Position
11.2.2 Vespa Company Profile and Main Business
11.2.3 Vespa Large-Scale Vector Indexing System Models, Specifications, and Application
11.2.4 Vespa Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.2.5 Vespa Recent Developments
11.3 Zilliz
11.3.1 Zilliz Company Information, Head Office, Market Area, and Industry Position
11.3.2 Zilliz Company Profile and Main Business
11.3.3 Zilliz Large-Scale Vector Indexing System Models, Specifications, and Application
11.3.4 Zilliz Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.3.5 Zilliz Recent Developments
11.4 Weaviate
11.4.1 Weaviate Company Information, Head Office, Market Area, and Industry Position
11.4.2 Weaviate Company Profile and Main Business
11.4.3 Weaviate Large-Scale Vector Indexing System Models, Specifications, and Application
11.4.4 Weaviate Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.4.5 Weaviate Recent Developments
11.5 Elastic
11.5.1 Elastic Company Information, Head Office, Market Area, and Industry Position
11.5.2 Elastic Company Profile and Main Business
11.5.3 Elastic Large-Scale Vector Indexing System Models, Specifications, and Application
11.5.4 Elastic Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.5.5 Elastic Recent Developments
11.6 Meta
11.6.1 Meta Company Information, Head Office, Market Area, and Industry Position
11.6.2 Meta Company Profile and Main Business
11.6.3 Meta Large-Scale Vector Indexing System Models, Specifications, and Application
11.6.4 Meta Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.6.5 Meta Recent Developments
11.7 Microsoft
11.7.1 Microsoft Company Information, Head Office, Market Area, and Industry Position
11.7.2 Microsoft Company Profile and Main Business
11.7.3 Microsoft Large-Scale Vector Indexing System Models, Specifications, and Application
11.7.4 Microsoft Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.7.5 Microsoft Recent Developments
11.8 Qdrant
11.8.1 Qdrant Company Information, Head Office, Market Area, and Industry Position
11.8.2 Qdrant Company Profile and Main Business
11.8.3 Qdrant Large-Scale Vector Indexing System Models, Specifications, and Application
11.8.4 Qdrant Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.8.5 Qdrant Recent Developments
11.9 Spotify
11.9.1 Spotify Company Information, Head Office, Market Area, and Industry Position
11.9.2 Spotify Company Profile and Main Business
11.9.3 Spotify Large-Scale Vector Indexing System Models, Specifications, and Application
11.9.4 Spotify Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.9.5 Spotify Recent Developments
11.10 Amazon Web Services
11.10.1 Amazon Web Services Company Information, Head Office, Market Area, and Industry Position
11.10.2 Amazon Web Services Company Profile and Main Business
11.10.3 Amazon Web Services Large-Scale Vector Indexing System Models, Specifications, and Application
11.10.4 Amazon Web Services Large-Scale Vector Indexing System Revenue and Gross Margin, 2020-2025
11.10.5 Amazon Web Services Recent Developments

12 Conclusion

13 Appendix
13.1 Research Methodology
13.2 Data Source
13.2.1 Secondary Sources
13.2.2 Primary Sources
13.3 Market Estimation Model
13.4 Disclaimer

According to YH Research, the global market for Large-Scale Vector Indexing System should grow from US$ 3311 million in 2024 to US$ 16035 million by 2031, with a CAGR of 26.5% for the period of 2025-2031.

Large-scale vector indexing systems are specialized technologies for the efficient storage, management, and retrieval of massive amounts of high-dimensional vector data. By constructing index structures (such as inverted indexes, hierarchical approximate nearest neighbor, and quantized encoding), they enable rapid similarity searches and near nearest neighbor (ANN) queries on vectors, quickly finding the most similar object to a given vector within a vast amount of data. This system is widely used in artificial intelligence scenarios, such as semantic search, recommendation systems, image and video retrieval, and natural language processing. It can support datasets ranging from tens of millions to billions of data points, achieving high-performance, low-latency query services while maintaining retrieval accuracy. It is a crucial infrastructure for enterprises building intelligent applications and processing large-scale AI data.

Large-Scale Vector Indexing System

Unit: US$ M

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In-depth insight into market trends

The downstream applications of large-scale vector indexing systems primarily include artificial intelligence companies, machine learning and deep learning platforms, recommendation system providers, search engines, natural language processing (NLP) applications, computer vision, intelligent security, financial risk control, medical image analysis, e-commerce and social platforms, and various other application scenarios requiring efficient similarity searches and vector retrieval. These downstream customers utilize vector indexing systems to perform rapid matching, feature retrieval, similarity calculation, and intelligent recommendation of massive amounts of data, thereby improving model inference efficiency, search accuracy, and user experience. They also support complex tasks such as personalized recommendations, image/video retrieval, semantic search, and large-scale model applications. In downstream businesses, vector indexing systems typically serve as the infrastructure layer, undertaking core computing and storage optimization functions. Their performance and stability directly impact the response speed and intelligence level of downstream products. The gross profit margin for large-scale vector indexing systems is approximately 50%.

Large-scale vector indexing systems, as a core infrastructure in the era of artificial intelligence and big data, are gradually moving from academic research to industrial applications, and their importance is becoming increasingly prominent. With the development of technologies such as deep learning, natural language processing, and computer vision, massive amounts of unstructured data (such as text, images, audio/video, and sensor data) are becoming increasingly prevalent in intelligent applications. Traditional relational databases and keyword-based retrieval methods are insufficient to meet the demands of high-dimensional feature similarity searches. Therefore, large-scale vector indexing systems have emerged, providing efficient, low-latency, and scalable vector storage and retrieval capabilities. They not only support scenarios such as search engines, recommendation systems, and intelligent question answering, but also serve as the foundation for large-scale model inference, semantic search, multimodal data fusion, and real-time decision-making. In the process of industrialization, domestic and international manufacturers are optimizing indexing algorithms, compression technologies, and distributed storage architectures to improve throughput and retrieval accuracy while reducing costs and hardware dependence. In the future, as the scale of AI models continues to grow and application scenarios diversify, vector indexing systems will further develop towards "one-stop, high-performance, and intelligent" solutions. Their ecosystem development, standardized interfaces, cloud-based services, and security compliance will become key factors in industry competition and innovation, having a profound impact on the entire field of intelligent data processing and knowledge discovery.

This report studies and analyses global Large-Scale Vector Indexing System status and future trends, to help determine the Large-Scale Vector Indexing System market size of the total market opportunity by Type, by Application, by company, and by region & country. This report is a detailed and comprehensive analysis of the world market for Large-Scale Vector Indexing System, and provides market size (US$ million) and Year-over-Year growth, considering 2023 as the base year.

For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.

To assess the competitive environment within the market including supplier revenue, market share, and company profiles.

Highlights
(1) Global Large-Scale Vector Indexing System market size, history data 2019-2024, and forecast data 2025 -2030, (US$ million)
(2) Global Large-Scale Vector Indexing System by company, revenue, market share and industry ranking 2019-2024, (US$ million)
(3) China Large-Scale Vector Indexing System by company, revenue, market share and industry ranking 2019-2024, (US$ million)
(4) Global Large-Scale Vector Indexing System key consuming regions, consumption value and demand structure
(5) Large-Scale Vector Indexing System industry chains, upstream, midstream and downstream
Market segment by players, this report covers
Pinecone
Vespa
Zilliz
Weaviate
Elastic
Meta
Microsoft
Qdrant
Spotify
Amazon Web Services

Market segment by Type, covers
Cloud-Based
Local Deployment

Market segment by Application, can be divided into
Enterprise
Individual

Market segment by regions, regional analysis covers
North America (United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia, and Rest of Asia-Pacific)
South America (Brazil, Rest of South America)
Middle East & Africa
Report Includes:
Chapter 1: to describe Large-Scale Vector Indexing System product scope, global consumption value, China consumption value, development opportunities, challenges, trends, and policies.
Chapter 2: Global Large-Scale Vector Indexing System market share and ranking of major manufacturers, revenue, 2019-2024
Chapter 3: China Large-Scale Vector Indexing System market share and ranking of major manufacturers, revenue, 2019-2024
Chapter 4: Large-Scale Vector Indexing System industry chain, upstream, medium-stream, and downstream.
Chapter 5: Segment by Type, consumption value, percent & CAGR, 2019-2030
Chapter 6: Segment by Application, consumption value, percent & CAGR, 2019-2030
Chapter 7: Segment in regional level, consumption value, percent & CAGR, 2019-2030
Chapter 8: Segment in country level, consumption value, percent & CAGR, 2019-2030
Chapter 9: Company profile, introducing the basic situation of the main companies in the market in detail, including product specifications, application, recent development, revenue, gross margin.
Chapter 10: Conclusions