벡터 데이터베이스 시장 규모 조사 및 예측 : 제공 제품별, 기술별, 산업별, 지역별 분석(2023-2030년)

Global Vector Database Market is valued approximately USD 1.20 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 23.30% over the forecast period 2023-2030. Vector Database is a type of database that is designed to store and manage vector data efficiently. In the context of databases, "vector" typically refers to a data structure used to represent geometric entities such as points, lines, and polygons in a multi-dimensional space. The Vector Database market is expanding because of factors such as rising demand of electronic health records and increasing number of data center. Vector databases are commonly used in geographic information systems, computer-aided design, and other applications where spatial or geometric data is a central component. As a result, the demand of Vector Database has progressively increased in the international market during the forecast period 2023-2030.

EHR systems often generate diverse data types, including text, images, and numerical values. Vector Databases can facilitate the integration of these diverse data types into a cohesive and structured format. According to the Statista, the global electronic health records (EHR) industry was valued at roughly USD 29 billion in 2020 and the market for EHRs is expected to reach up to USD 47 billion by 2027. Furthermore, Vector Databases can enable interoperability between different healthcare systems and institutions by providing a standardized way to store and retrieve vector data. This is crucial for exchanging health information seamlessly. Another important factor drives the Vector Database market is increasing number of data center. Multiple data centers across different geographical locations enable better distribution and redundancy of data. Vector Databases can take advantage of this distributed infrastructure to provide low-latency access to data for users and applications across different regions. In addition, as per Statista, in 2023, the United States has the most data centers totaled 5,375, followed by Germany with 522 data centres and 517 in the United Kingdom. Moreover, growing deployment of cloud platforms by enterprises and technological advancement in database management platforms is anticipated to create a lucrative growth opportunity for the market over the forecast period. However, privacy and security of data stored on databases and lack of technical expertise is going to impede overall market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Vector Database Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 with largest market share owing to the increasing presence of key market players and data centers can indeed significantly support the growth of Vector Databases in the region. The presence of key market players, including established technology companies and database providers, can bring credibility and validation to Vector Databases. The region's dominant performance is anticipated to propel the overall demand of Vector Database. Furthermore, Asia Pacific is expected to grow fastest during the forecast period, owing to factors such as adoption of advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) can significantly support the growth of Vector Databases in the region. AI applications, including machine learning models, often deal with high-dimensional vector data. Vector Databases can be used to store and retrieve these models efficiently.

Major market player included in this report are:

• Microsoft Corporation
• Elastic N.V.
• Alibaba Group
• MongoDB, Inc
• Redis Labs Ltd
• SingleStore, Inc
• Zilliz Inc
• Pinecone Systems, Inc
• Google LLC
• Amazon Web Services, Inc

Recent Developments in the Market:

• In November 2023, DataStax, a leading company in the realm of powering generative AI applications with real-time, scalable data, has unveiled an expanded partnership with Amazon Web Services (AWS). This collaboration encompasses a comprehensive fusion of groundbreaking generative artificial intelligence (AI) advancements, coupled with strategic initiatives in go-to-market strategies, product enhancements, and technology integrations. The synergy between the two entities aims to furnish customers with cutting-edge generative AI technologies, empowering them to enhance productivity and swiftly develop and deploy precise generative AI applications that elevate customer experiences. This partnership is poised to propel the adoption of generative AI offerings from both companies. The SCA is designed to expedite customer innovation by delivering potent technologies essential for large language model (LLM), AI assistant, and real-time generative AI projects. The collaboration extends beyond a mere business arrangement, as DataStax and AWS are set to embark on a global go-to-market initiative, leveraging their collective expertise and resources to co-build, co-market, and co-sell their respective AI products. This united effort aims to provide customers with a robust ecosystem that fosters the seamless integration of generative AI capabilities into their projects, thereby ushering in a new era of advanced and transformative applications.

Global Vector Database Market Report Scope:

• Historical Data: 2020 - 2021
• Base Year for Estimation: 2022
• Forecast period: 2023-2030
• Report Coverage: Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
• Segments Covered: Offering, Technology, Vertical, Region
• Regional Scope: North America; Europe; Asia Pacific; Latin America; Middle East & Africa
• Customization Scope: Free report customization (equivalent up to 8 analyst's working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below.

By Offering

• Solution
• Service

By Technology

• Natural Language Processing
• Computer Vision
• Recommendation Systems

By Vertical

• BFSI
• Retail & eCommerce
• Healthcare & Life Sciences
• IT & ITeS
• Media & Entertainment
• Manufacturing
• Other Verticals

By Region:

• North America
• U.S.
• Canada
• Europe
• UK
• Germany
• France
• Spain
• Italy
• ROE
• Asia Pacific
• China
• India
• Japan
• Australia
• South Korea
• RoAPAC
• Latin America
• Brazil
• Mexico
• Middle East & Africa
• Saudi Arabia
• South Africa
• Rest of Middle East & Africa

Table of Contents

Chapter 1. Executive Summary

• 1.1. Market Snapshot
• 1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
  • 1.2.1. Vector Database Market, by region, 2020-2030 (USD Billion)
  • 1.2.2. Vector Database Market, by Offering, 2020-2030 (USD Billion)
  • 1.2.3. Vector Database Market, by Technology, 2020-2030 (USD Billion)
  • 1.2.4. Vector Database Market, by Vertical, 2020-2030 (USD Billion)
• 1.3. Key Trends
• 1.4. Estimation Methodology
• 1.5. Research Assumption

Chapter 2. Global Vector Database Market Definition and Scope

• 2.1. Objective of the Study
• 2.2. Market Definition & Scope
  • 2.2.1. Industry Evolution
  • 2.2.2. Scope of the Study
• 2.3. Years Considered for the Study
• 2.4. Currency Conversion Rates

Chapter 3. Global Vector Database Market Dynamics

• 3.1. Vector Database Market Impact Analysis (2020-2030)
  • 3.1.1. Market Drivers
    • 3.1.1.1. Rising demand of electronic health records
    • 3.1.1.2. Increasing number of data centre
  • 3.1.2. Market Challenges
    • 3.1.2.1. Privacy and security of data stored on databases
    • 3.1.2.2. Lack of technical expertise
  • 3.1.3. Market Opportunities
    • 3.1.3.1. Growing deployment of cloud platforms by enterprises
    • 3.1.3.2. Technological advancement in database management platforms

Chapter 4. Global Vector Database Market: Industry Analysis

• 4.1. Porter's 5 Force Model
  • 4.1.1. Bargaining Power of Suppliers
  • 4.1.2. Bargaining Power of Buyers
  • 4.1.3. Threat of New Entrants
  • 4.1.4. Threat of Substitutes
  • 4.1.5. Competitive Rivalry
• 4.2. Porter's 5 Force Impact Analysis
• 4.3. PEST Analysis
  • 4.3.1. Political
  • 4.3.2. Economic
  • 4.3.3. Social
  • 4.3.4. Technological
  • 4.3.5. Environmental
  • 4.3.6. Legal
• 4.4. Top investment opportunity
• 4.5. Top winning strategies
• 4.6. COVID-19 Impact Analysis
• 4.7. Disruptive Trends
• 4.8. Industry Expert Perspective
• 4.9. Analyst Recommendation & Conclusion

Chapter 5. Global Vector Database Market, by Offering

• 5.1. Market Snapshot
• 5.2. Global Vector Database Market by Offering, Performance - Potential Analysis
• 5.3. Global Vector Database Market Estimates & Forecasts by Offering 2020-2030 (USD Billion)
• 5.4. Vector Database Market, Sub Segment Analysis
  • 5.4.1. Solution
  • 5.4.2. Service

Chapter 6. Global Vector Database Market, by Technology

• 6.1. Market Snapshot
• 6.2. Global Vector Database Market by Technology, Performance - Potential Analysis
• 6.3. Global Vector Database Market Estimates & Forecasts by Technology 2020-2030 (USD Billion)
• 6.4. Vector Database Market, Sub Segment Analysis
  • 6.4.1. Natural Language Processing
  • 6.4.2. Computer Vision
  • 6.4.3. Recommendation Systems

Chapter 7. Global Vector Database Market, by Vertical

• 7.1. Market Snapshot
• 7.2. Global Vector Database Market by Vertical, Performance - Potential Analysis
• 7.3. Global Vector Database Market Estimates & Forecasts by Vertical 2020-2030 (USD Billion)
• 7.4. Vector Database Market, Sub Segment Analysis
  • 7.4.1. BFSI
  • 7.4.2. Retail & eCommerce
  • 7.4.3. Healthcare & Life Sciences
  • 7.4.4. IT & ITeS
  • 7.4.5. Media & Entertainment
  • 7.4.6. Manufacturing
  • 7.4.7. Other Verticals

Chapter 8. Global Vector Database Market, Regional Analysis

• 8.1. Top Leading Countries
• 8.2. Top Emerging Countries
• 8.3. Vector Database Market, Regional Market Snapshot
• 8.4. North America Vector Database Market
  • 8.4.1. U.S. Vector Database Market
    • 8.4.1.1. Offering breakdown estimates & forecasts, 2020-2030
    • 8.4.1.2. Technology breakdown estimates & forecasts, 2020-2030
    • 8.4.1.3. Vertical breakdown estimates & forecasts, 2020-2030
  • 8.4.2. Canada Vector Database Market
• 8.5. Europe Vector Database Market Snapshot
  • 8.5.1. U.K. Vector Database Market
  • 8.5.2. Germany Vector Database Market
  • 8.5.3. France Vector Database Market
  • 8.5.4. Spain Vector Database Market
  • 8.5.5. Italy Vector Database Market
  • 8.5.6. Rest of Europe Vector Database Market
• 8.6. Asia-Pacific Vector Database Market Snapshot
  • 8.6.1. China Vector Database Market
  • 8.6.2. India Vector Database Market
  • 8.6.3. Japan Vector Database Market
  • 8.6.4. Australia Vector Database Market
  • 8.6.5. South Korea Vector Database Market
  • 8.6.6. Rest of Asia Pacific Vector Database Market
• 8.7. Latin America Vector Database Market Snapshot
  • 8.7.1. Brazil Vector Database Market
  • 8.7.2. Mexico Vector Database Market
• 8.8. Middle East & Africa Vector Database Market
  • 8.8.1. Saudi Arabia Vector Database Market
  • 8.8.2. South Africa Vector Database Market
  • 8.8.3. Rest of Middle East & Africa Vector Database Market

Chapter 9. Competitive Intelligence

• 9.1. Key Company SWOT Analysis
  • 9.1.1. Company 1
  • 9.1.2. Company 2
  • 9.1.3. Company 3
• 9.2. Top Market Strategies
• 9.3. Company Profiles
  • 9.3.1. Microsoft Corporation
    • 9.3.1.1. Key Information
    • 9.3.1.2. Overview
    • 9.3.1.3. Financial (Subject to Data Availability)
    • 9.3.1.4. Product Summary
    • 9.3.1.5. Recent Developments
  • 9.3.2. Elastic N.V.
  • 9.3.3. Alibaba Group
  • 9.3.4. MongoDB, Inc
  • 9.3.5. Redis Labs Ltd
  • 9.3.6. SingleStore, Inc
  • 9.3.7. Zilliz Inc
  • 9.3.8. Pinecone Systems, Inc
  • 9.3.9. Google LLC
  • 9.3.10. Amazon Web Services, Inc

Chapter 10. Research Process

• 10.1. Research Process
  • 10.1.1. Data Mining
  • 10.1.2. Analysis
  • 10.1.3. Market Estimation
  • 10.1.4. Validation
  • 10.1.5. Publishing
• 10.2. Research Attributes
• 10.3. Research Assumption