세계의 벡터 데이터베이스 솔루션 시장 : 시장 점유율과 순위, 전체 판매 및 수요 예측(2025-2031년)

The global market for Vector Database Solution was estimated to be worth US$ 3892 million in 2024 and is forecast to a readjusted size of US$ 15725 million by 2031 with a CAGR of 22.6% during the forecast period 2025-2031.

Vector Database Solution is a database system designed and optimized to process and store vector data. Vector data refers to data with magnitude and direction, such as geometric data, geospatial data, time series data, etc. Traditional relational databases are usually more suitable for processing scalar data, while vector databases focus on efficiently processing vector data, providing faster and more flexible query and analysis capabilities.

As technologies such as artificial intelligence, image recognition, large language models (LLMs) and recommendation systems place higher and higher demands on high-dimensional vector data management and search performance, vector database solutions are rapidly becoming a key component of the next-generation data infrastructure. This type of solution is mainly divided into two categories: cloud-based hosting deployment and local private deployment: the former is suitable for small and medium-sized enterprises or individual developers, with the advantages of elastic expansion, convenient access and rapid iteration, while the latter is more suitable for large enterprises with strict requirements on data sovereignty and privacy compliance, and can achieve stronger performance optimization and customized integration. At the application level, vector databases are widely used in scenarios such as natural language retrieval, image and video content search, personalized recommendation, and knowledge question-and-answer systems, bringing a more natural interactive experience to individual users and providing enterprises with smarter data retrieval and analysis capabilities.

The core vendors of global vector database solutions include Zilliz, Faiss and Redis, and the top three vendors account for about 40% of the global market share. North America is the largest market, accounting for about 37% of the market share. In terms of product types, cloud-based is the largest segment, accounting for about 65% of the share. At the same time, in terms of downstream, enterprises are the largest downstream field, accounting for about 80% of the share.

In the future, with the widespread application of multimodal AI models, the type and volume of vectorized data will continue to grow, pushing vector databases from "acceleration engines" to "cognitive infrastructure". Under this trend, database vendors need to make early arrangements in the following aspects: First, build a GPU-friendly heterogeneous computing support framework to improve the efficiency of vector indexing and approximate search above one billion levels; second, strengthen native integration with RAG architectures such as large language models (such as ChatGPT and Claude) to become the memory center of AI Agent; third, around security, compliance and explainability, develop support for ACL, audit logs, end-to-end encryption and other functions to meet enterprise-level deployment requirements; fourth, promote standardized interfaces and ecological integration, seamlessly connect with mainstream data lakes and MLOps platforms, and form a general knowledge retrieval infrastructure.

In short, vector databases are evolving from "AI search tools" to "key hubs of intelligent data systems", and their future development will be deeply tied to the evolution path of the big model ecosystem. Only by continuously investing in breakthroughs in underlying indexing technology, heterogeneous computing optimization, and cloud-native architecture innovation can manufacturers truly stand out and seize the commanding heights of future intelligent data infrastructure.

This report aims to provide a comprehensive presentation of the global market for Vector Database Solution, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Vector Database Solution by region & country, by Type, and by Application.

The Vector Database Solution market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Vector Database Solution.

Market Segmentation

By Company

• Zilliz
• Faiss
• Redis
• Tinybird
• Vespa
• Vald
• Pinecone
• Weaviate
• Amazon Web Services
• Solix Technologies

Segment by Type

• Cloud Based
• On-Premises

Segment by Application

• Personal
• Enterprise

By Region

• North America
  • United States
  • Canada
• Asia-Pacific
  • China
  • Japan
  • South Korea
  • Southeast Asia
  • India
  • Australia
  • Rest of Asia-Pacific
• Europe
  • Germany
  • France
  • U.K.
  • Italy
  • Netherlands
  • Nordic Countries
  • Rest of Europe
• Latin America
  • Mexico
  • Brazil
  • Rest of Latin America
• Middle East & Africa
  • Turkey
  • Saudi Arabia
  • UAE
  • Rest of MEA

Chapter Outline

Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.

Chapter 2: Detailed analysis of Vector Database Solution company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.

Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.

Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.

Chapter 5: Revenue of Vector Database Solution in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.

Chapter 6: Revenue of Vector Database Solution in country level. It provides sigmate data by Type, and by Application for each country/region.

Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.

Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.

Chapter 9: Conclusion.

Table of Contents

1 Market Overview

• 1.1 Vector Database Solution Product Introduction
• 1.2 Global Vector Database Solution Market Size Forecast (2020-2031)
• 1.3 Vector Database Solution Market Trends & Drivers
  • 1.3.1 Vector Database Solution Industry Trends
  • 1.3.2 Vector Database Solution Market Drivers & Opportunity
  • 1.3.3 Vector Database Solution Market Challenges
  • 1.3.4 Vector Database Solution Market Restraints
• 1.4 Assumptions and Limitations
• 1.5 Study Objectives
• 1.6 Years Considered

2 Competitive Analysis by Company

• 2.1 Global Vector Database Solution Players Revenue Ranking (2024)
• 2.2 Global Vector Database Solution Revenue by Company (2020-2025)
• 2.3 Key Companies Vector Database Solution Manufacturing Base Distribution and Headquarters
• 2.4 Key Companies Vector Database Solution Product Offered
• 2.5 Key Companies Time to Begin Mass Production of Vector Database Solution
• 2.6 Vector Database Solution Market Competitive Analysis
  • 2.6.1 Vector Database Solution Market Concentration Rate (2020-2025)
  • 2.6.2 Global 5 and 10 Largest Companies by Vector Database Solution Revenue in 2024
  • 2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Vector Database Solution as of 2024)
• 2.7 Mergers & Acquisitions, Expansion

3 Segmentation by Type

• 3.1 Introduction by Type
  • 3.1.1 Cloud Based
  • 3.1.2 On-Premises
• 3.2 Global Vector Database Solution Sales Value by Type
  • 3.2.1 Global Vector Database Solution Sales Value by Type (2020 VS 2024 VS 2031)
  • 3.2.2 Global Vector Database Solution Sales Value, by Type (2020-2031)
  • 3.2.3 Global Vector Database Solution Sales Value, by Type (%) (2020-2031)

4 Segmentation by Application

• 4.1 Introduction by Application
  • 4.1.1 Personal
  • 4.1.2 Enterprise
• 4.2 Global Vector Database Solution Sales Value by Application
  • 4.2.1 Global Vector Database Solution Sales Value by Application (2020 VS 2024 VS 2031)
  • 4.2.2 Global Vector Database Solution Sales Value, by Application (2020-2031)
  • 4.2.3 Global Vector Database Solution Sales Value, by Application (%) (2020-2031)

5 Segmentation by Region

• 5.1 Global Vector Database Solution Sales Value by Region
  • 5.1.1 Global Vector Database Solution Sales Value by Region: 2020 VS 2024 VS 2031
  • 5.1.2 Global Vector Database Solution Sales Value by Region (2020-2025)
  • 5.1.3 Global Vector Database Solution Sales Value by Region (2026-2031)
  • 5.1.4 Global Vector Database Solution Sales Value by Region (%), (2020-2031)
• 5.2 North America
  • 5.2.1 North America Vector Database Solution Sales Value, 2020-2031
  • 5.2.2 North America Vector Database Solution Sales Value by Country (%), 2024 VS 2031
• 5.3 Europe
  • 5.3.1 Europe Vector Database Solution Sales Value, 2020-2031
  • 5.3.2 Europe Vector Database Solution Sales Value by Country (%), 2024 VS 2031
• 5.4 Asia Pacific
  • 5.4.1 Asia Pacific Vector Database Solution Sales Value, 2020-2031
  • 5.4.2 Asia Pacific Vector Database Solution Sales Value by Region (%), 2024 VS 2031
• 5.5 South America
  • 5.5.1 South America Vector Database Solution Sales Value, 2020-2031
  • 5.5.2 South America Vector Database Solution Sales Value by Country (%), 2024 VS 2031
• 5.6 Middle East & Africa
  • 5.6.1 Middle East & Africa Vector Database Solution Sales Value, 2020-2031
  • 5.6.2 Middle East & Africa Vector Database Solution Sales Value by Country (%), 2024 VS 2031

6 Segmentation by Key Countries/Regions

• 6.1 Key Countries/Regions Vector Database Solution Sales Value Growth Trends, 2020 VS 2024 VS 2031
• 6.2 Key Countries/Regions Vector Database Solution Sales Value, 2020-2031
• 6.3 United States
  • 6.3.1 United States Vector Database Solution Sales Value, 2020-2031
  • 6.3.2 United States Vector Database Solution Sales Value by Type (%), 2024 VS 2031
  • 6.3.3 United States Vector Database Solution Sales Value by Application, 2024 VS 2031
• 6.4 Europe
  • 6.4.1 Europe Vector Database Solution Sales Value, 2020-2031
  • 6.4.2 Europe Vector Database Solution Sales Value by Type (%), 2024 VS 2031
  • 6.4.3 Europe Vector Database Solution Sales Value by Application, 2024 VS 2031
• 6.5 China
  • 6.5.1 China Vector Database Solution Sales Value, 2020-2031
  • 6.5.2 China Vector Database Solution Sales Value by Type (%), 2024 VS 2031
  • 6.5.3 China Vector Database Solution Sales Value by Application, 2024 VS 2031
• 6.6 Japan
  • 6.6.1 Japan Vector Database Solution Sales Value, 2020-2031
  • 6.6.2 Japan Vector Database Solution Sales Value by Type (%), 2024 VS 2031
  • 6.6.3 Japan Vector Database Solution Sales Value by Application, 2024 VS 2031
• 6.7 South Korea
  • 6.7.1 South Korea Vector Database Solution Sales Value, 2020-2031
  • 6.7.2 South Korea Vector Database Solution Sales Value by Type (%), 2024 VS 2031
  • 6.7.3 South Korea Vector Database Solution Sales Value by Application, 2024 VS 2031
• 6.8 Southeast Asia
  • 6.8.1 Southeast Asia Vector Database Solution Sales Value, 2020-2031
  • 6.8.2 Southeast Asia Vector Database Solution Sales Value by Type (%), 2024 VS 2031
  • 6.8.3 Southeast Asia Vector Database Solution Sales Value by Application, 2024 VS 2031
• 6.9 India
  • 6.9.1 India Vector Database Solution Sales Value, 2020-2031
  • 6.9.2 India Vector Database Solution Sales Value by Type (%), 2024 VS 2031
  • 6.9.3 India Vector Database Solution Sales Value by Application, 2024 VS 2031

7 Company Profiles

• 7.1 Zilliz
  • 7.1.1 Zilliz Profile
  • 7.1.2 Zilliz Main Business
  • 7.1.3 Zilliz Vector Database Solution Products, Services and Solutions
  • 7.1.4 Zilliz Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.1.5 Zilliz Recent Developments
• 7.2 Faiss
  • 7.2.1 Faiss Profile
  • 7.2.2 Faiss Main Business
  • 7.2.3 Faiss Vector Database Solution Products, Services and Solutions
  • 7.2.4 Faiss Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.2.5 Faiss Recent Developments
• 7.3 Redis
  • 7.3.1 Redis Profile
  • 7.3.2 Redis Main Business
  • 7.3.3 Redis Vector Database Solution Products, Services and Solutions
  • 7.3.4 Redis Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.3.5 Redis Recent Developments
• 7.4 Tinybird
  • 7.4.1 Tinybird Profile
  • 7.4.2 Tinybird Main Business
  • 7.4.3 Tinybird Vector Database Solution Products, Services and Solutions
  • 7.4.4 Tinybird Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.4.5 Tinybird Recent Developments
• 7.5 Vespa
  • 7.5.1 Vespa Profile
  • 7.5.2 Vespa Main Business
  • 7.5.3 Vespa Vector Database Solution Products, Services and Solutions
  • 7.5.4 Vespa Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.5.5 Vespa Recent Developments
• 7.6 Vald
  • 7.6.1 Vald Profile
  • 7.6.2 Vald Main Business
  • 7.6.3 Vald Vector Database Solution Products, Services and Solutions
  • 7.6.4 Vald Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.6.5 Vald Recent Developments
• 7.7 Pinecone
  • 7.7.1 Pinecone Profile
  • 7.7.2 Pinecone Main Business
  • 7.7.3 Pinecone Vector Database Solution Products, Services and Solutions
  • 7.7.4 Pinecone Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.7.5 Pinecone Recent Developments
• 7.8 Weaviate
  • 7.8.1 Weaviate Profile
  • 7.8.2 Weaviate Main Business
  • 7.8.3 Weaviate Vector Database Solution Products, Services and Solutions
  • 7.8.4 Weaviate Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.8.5 Weaviate Recent Developments
• 7.9 Amazon Web Services
  • 7.9.1 Amazon Web Services Profile
  • 7.9.2 Amazon Web Services Main Business
  • 7.9.3 Amazon Web Services Vector Database Solution Products, Services and Solutions
  • 7.9.4 Amazon Web Services Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.9.5 Amazon Web Services Recent Developments
• 7.10 Solix Technologies
  • 7.10.1 Solix Technologies Profile
  • 7.10.2 Solix Technologies Main Business
  • 7.10.3 Solix Technologies Vector Database Solution Products, Services and Solutions
  • 7.10.4 Solix Technologies Vector Database Solution Revenue (US$ Million) & (2020-2025)
  • 7.10.5 Solix Technologies Recent Developments

8 Industry Chain Analysis

• 8.1 Vector Database Solution Industrial Chain
• 8.2 Vector Database Solution Upstream Analysis
  • 8.2.1 Key Raw Materials
  • 8.2.2 Raw Materials Key Suppliers
  • 8.2.3 Manufacturing Cost Structure
• 8.3 Midstream Analysis
• 8.4 Downstream Analysis (Customers Analysis)
• 8.5 Sales Model and Sales Channels
  • 8.5.1 Vector Database Solution Sales Model
  • 8.5.2 Sales Channel
  • 8.5.3 Vector Database Solution Distributors

9 Research Findings and Conclusion

10 Appendix

• 10.1 Research Methodology
  • 10.1.1 Methodology/Research Approach
    • 10.1.1.1 Research Programs/Design
    • 10.1.1.2 Market Size Estimation
    • 10.1.1.3 Market Breakdown and Data Triangulation
  • 10.1.2 Data Source
    • 10.1.2.1 Secondary Sources
    • 10.1.2.2 Primary Sources
• 10.2 Author Details
• 10.3 Disclaimer