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市場調查報告書
商品編碼
2111080

雲端原生資料庫市場預測至 2034 年—按資料庫類型、部署模型、服務模型、工作負載、應用程式、最終用戶和地區分類的全球分析

Cloud-Native Database Market Forecasts to 2034 - Global Analysis By Database Type, Deployment Model, Service Model, Workload, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球雲端原生資料庫市場預計將在 2026 年達到 126 億美元，到 2034 年達到 584 億美元，在預測期內複合年成長率為 21.1%。

雲端原生資料庫是專為充分利用雲端運算特性而設計的資料庫系統，例如彈性可擴展性、分散式架構和自動化管理，使組織能夠運行高可用性和容錯性的資料庫工作負載。這些資料庫支援多種類型，包括關聯式資料庫、NoSQL（文件型、鍵值型、寬列型和圖型）、分散式 SQL、時序資料庫、多模型資料庫和記憶體內，並透過公有雲、私有雲、混合雲和多重雲端部署模型交付。透過利用雲端原生架構的原則，這項技術可幫助組織實現可擴展性、高可用性和營運效率。

雲端原生應用架構的廣泛應用

雲端原生應用架構和微服務的日益普及是推動雲端原生資料庫市場發展的主要動力。企業正在利用容器、Kubernetes 和無伺服器運算等技術實現應用現代化，這需要專為雲端環境設計的資料庫。雲端原生資料庫提供彈性擴展、自動容錯移轉以及與現代應用模式相契合的分散式架構。資料庫資源能夠獨立於運算和儲存進行擴展，從而降低成本。隨著企業加速雲端遷移和應用程式現代化，對雲端原生資料庫的需求將持續顯著成長。

對資料遷移的複雜性和供應商鎖定問題感到擔憂。

資料遷移的複雜性以及對供應商鎖定的擔憂是限制雲端原生資料庫市場發展的主要因素。將傳統資料庫工作負載遷移到雲端原生平台需要精心規劃和執行，以確保資料完整性和應用程式相容性。企業擔心對特定雲端供應商的依賴以及平台間資料遷移的難度。資料儲存位置要求和監管合規性也使雲端資料庫的採用變得更加複雜。這些挑戰可能導致部署延遲和實施成本增加。

人工智慧與自主資料庫能力的整合

人工智慧與自主資料庫功能的融合為雲端原生資料庫市場帶來了巨大的機會。人工智慧驅動的資料庫系統能夠根據工作負載模式自動最佳化效能、調整查詢並管理擴充。自主功能降低了維運開銷，並實現了資料庫的自主運作。隨著企業尋求降低資料庫管理成本並提升效能，對智慧雲端原生資料庫的需求持續成長，這為人工智慧驅動的資料庫解決方案供應商創造了龐大的商機。

與開放原始碼和替代資料庫解決方案的競爭

來自開放原始碼和替代資料庫解決方案的競爭對雲端原生資料庫市場構成重大威脅。企業可能會採用開放原始碼資料庫來避免供應商鎖定並降低成本。託管式開放原始碼資料庫服務的出現為商業產品提供了替代方案。資料庫選擇的多樣化可能會對特定雲端原生資料庫解決方案的定價和採用率造成壓力。

新型冠狀病毒（COVID-19）的影響：

新冠疫情加速了雲端原生資料庫的普及，各組織機構迅速實現營運數位化，並遷移到雲端環境以支援遠端辦公、數位服務和應用現代化。應用工作負載和資料量的激增催生了對可擴展、容錯性強的資料庫解決方案的需求。各組織機構也意識到傳統資料庫在支援雲端原生資料庫開發方面的限制。疫情凸顯了雲端原生資料庫在推動數位轉型、增強市場長期成長以及使其成為現代企業不可或缺的基礎設施方面的關鍵作用。

在預測期內，關聯資料庫領域預計將佔據最大的市場佔有率。

在預測期內，關聯資料庫預計將佔據最大的市場佔有率。這主要歸功於對符合 ACID 標準的結構化資料管理在事務型應用和企業系統中的持續需求。關聯資料庫提供成熟的查詢功能、強一致性和久經考驗的可靠性，這些對於許多企業應用而言仍然至關重要。主流雲端服務供應商提供的雲端原生關聯資料庫服務也鞏固了其市場主導地位。隨著企業對舊有應用程式進行現代化改造，關聯資料庫仍是事務型工作負載的首選。

在預測期內，分散式 SQL資料庫領域預計將呈現最高的複合年成長率。

在預測期內，分散式 SQL資料庫領域預計將呈現最高的成長率，這主要得益於市場對兼具 NoSQL 可擴展性和 SQL 關係型及 ACID 特性的資料庫需求不斷成長。分散式 SQL資料庫支援跨雲區域的橫向擴展，同時保持強一致性和關係型功能。全球分散式應用和多區域部署的日益普及正在推動這一需求。隨著企業需要能夠突破單節點限制並維持關係型功能的資料庫，分散式 SQL資料庫的應用範圍也持續擴大。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於該地區雲端技術的廣泛應用、主要雲端服務提供商的存在以及對雲端原生資料庫技術的早期採用。該地區對應用現代化和數位轉型的重視，催生了對全面雲端原生資料庫解決方案的需求。在科技、金融服務和醫療保健等對資料庫可擴展性和容錯性要求極高的產業，北美積極採用雲端原生資料庫技術，進一步鞏固了其市場主導地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於雲端運算的快速普及、科技產業的擴張以及主要經濟體對數位基礎設施投資的增加。隨著企業對其應用程式架構進行現代化改造，中國、印度和日本等國家在雲端原生資料庫的採用方面正經歷顯著成長。隨著雲端運算的普及、本地資料中心的建置以及應對日益成長的應用工作負載的需求，亞太地區正成為雲端原生資料庫市場的主要驅動力。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 主要參與者（最多3家公司）的SWOT分析
  • 區域分類
    • 根據客戶要求，我們可以提供主要國家的市場估算和預測，以及複合年成長率（註：需經可行性確認）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球雲端原生資料庫市場：依資料庫類型分類

  • 關聯資料庫
  • NoSQL資料庫
    • 文件資料資料庫
    • 鍵值資料庫
    • 寬列資料庫
    • 圖資料庫
  • 分散式 SQL資料庫
  • 時間序列資料庫
  • 多模型資料庫
  • 記憶體內資料庫

第6章 全球雲端原生資料庫市場：依部署模式分類

  • 公共雲端
  • 私有雲端
  • 混合雲端
  • 多重雲端

第7章：全球雲端原生資料庫市場：依服務模式分類

  • 完全託管資料庫
  • 自管理資料庫

第8章 全球雲端原生資料庫市場：依工作負載分類

  • 事務處理（OLTP）
  • 分析處理（OLAP）
  • 混合事務/分析處理（HTAP）
  • 即時分析
  • 人工智慧和機器學習工作負載

第9章：全球雲端原生資料庫市場：按應用程式分類

  • 網頁和行動應用程式
  • 企業應用
  • 電子商務平台
  • 物聯網 (IoT)
  • 金融服務
  • 客戶分析
  • DevOps 和 CI/CD
  • 遊戲

第10章：全球雲端原生資料庫市場：以最終用戶分類

  • 銀行、金融服務和保險（BFSI）
  • 資訊科技與通訊
  • 零售與電子商務
  • 醫療保健和生命科學
  • 製造業
  • 政府/公共部門
  • 媒體與娛樂
  • 能源公用事業
  • 教育

第11章 全球雲端原生資料庫市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第12章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第13章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第14章：公司簡介

  • Amazon Web Services（AWS）
  • Microsoft
  • Google
  • Oracle
  • IBM
  • SAP
  • MongoDB
  • Cockroach Labs
  • Yugabyte
  • SingleStore
  • Snowflake
  • Couchbase
  • DataStax
  • Redis
  • PingCAP
Product Code: SMRC38780

According to Stratistics MRC, the Global Cloud-Native Database Market is accounted for $12.6 billion in 2026 and is expected to reach $58.4 billion by 2034, growing at a CAGR of 21.1% during the forecast period. Cloud-Native Databases are purpose-built database systems designed to leverage cloud computing capabilities, including elastic scalability, distributed architecture, and automated management, enabling organizations to run database workloads with high availability and resilience. These databases support multiple types including relational, NoSQL (document, key-value, wide-column, and graph), distributed SQL, time series, multi-model, and in-memory databases, delivered through public, private, hybrid, and multi-cloud deployment models. This technology helps organizations achieve scalability, high availability, and operational efficiency by leveraging cloud-native architecture principles.

Market Dynamics:

Driver:

Growing adoption of cloud-native application architectures

The increasing adoption of cloud-native application architectures and microservices serves as a primary driver for the Cloud-Native Database market. Organizations are modernizing applications using containers, Kubernetes, and serverless computing, requiring databases designed for cloud environments. Cloud-native databases provide elastic scaling, automated failover, and distributed architecture that align with modern application patterns. The ability to scale database resources independently of compute and storage reduces costs. As enterprises accelerate cloud migration and application modernization, the demand for cloud-native databases continues to expand significantly.

Restraint:

Data migration complexity and vendor lock-in concerns

Data migration complexity and vendor lock-in concerns pose significant restraints to the Cloud-Native Database market. Migrating legacy database workloads to cloud-native platforms requires careful planning and execution to ensure data integrity and application compatibility. Organizations worry about dependency on specific cloud providers and the difficulty of migrating data between platforms. Data residency requirements and regulatory compliance add complexity to cloud database deployments. These challenges can slow adoption and increase implementation costs.

Opportunity:

Integration of AI and autonomous database capabilities

The integration of AI and autonomous database capabilities presents significant opportunities for the Cloud-Native Database market. AI-powered database systems can automatically optimize performance, tune queries, and manage scaling based on workload patterns. Autonomous capabilities reduce operational overhead and enable self-driving database operations. As organizations seek to reduce database administration costs and improve performance, the demand for intelligent cloud-native databases continues to grow, creating substantial opportunities for providers offering AI-driven database solutions.

Threat:

Competition from open-source and alternative database solutions

Competition from open-source and alternative database solutions poses significant threats to the Cloud-Native Database market. Organizations may adopt open-source databases to avoid vendor lock-in and reduce costs. The availability of managed open-source database services provides alternatives to commercial offerings. The diversity of database options can pressure pricing and adoption of specific cloud-native database solutions.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of cloud-native databases as organizations rapidly digitized operations and migrated to cloud environments to support remote work, digital services, and application modernization. The surge in application workloads and data volumes created demand for scalable, resilient database solutions. Organizations recognized the limitations of traditional databases in supporting cloud-native application development. The pandemic ultimately highlighted the critical importance of cloud-native databases in enabling digital transformation, strengthening long-term market growth and positioning cloud-native databases as essential infrastructure for modern enterprises.

The relational database segment is expected to be the largest during the forecast period

The relational database segment is expected to account for the largest market share during the forecast period, driven by the continued demand for ACID-compliant, structured data management for transactional applications and enterprise systems. Relational databases provide mature query capabilities, strong consistency, and proven reliability that remain essential for many enterprise applications. The availability of cloud-native relational database services from major cloud providers supports continued dominance. As organizations modernize legacy applications, relational databases remain the primary choice for transactional workloads.

The distributed SQL database segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the distributed SQL database segment is predicted to witness the highest growth rate, due to the increasing demand for databases that combine the scalability of NoSQL with the relational and ACID capabilities of SQL. Distributed SQL databases enable horizontal scaling across cloud regions while maintaining strong consistency and relational capabilities. The growing adoption of globally distributed applications and multi-region deployments drives demand. As organizations require databases that scale beyond single-node limits while preserving relational features, distributed SQL continues to gain adoption.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, driven by substantial cloud adoption, the presence of major cloud providers, and early adoption of cloud-native database technologies. The region's focus on application modernization and digital transformation creates demand for comprehensive cloud-native database solutions. Strong adoption across technology, financial services, and healthcare sectors, where database scalability and resilience are critical, contributes to market leadership.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, fueled by rapid cloud adoption, expanding technology sectors, and growing investment in digital infrastructure across major economies. Countries such as China, India, and Japan are witnessing significant growth in cloud-native database adoption as organizations modernize application architectures. Rising cloud adoption, local data center build-outs, and the need to support growing application workloads position APAC as a key growth driver for the cloud-native database market.

Key players in the market

Some of the key players in the Cloud-Native Database Market include Amazon Web Services (AWS), Microsoft Corporation, Google LLC, Oracle Corporation, IBM Corporation, SAP SE, MongoDB Inc., Cockroach Labs Inc., Yugabyte Inc., SingleStore Inc., Snowflake Inc., Couchbase Inc., DataStax Inc., Redis Ltd., and PingCAP.

Key Developments:

In June 2026, AWS announced significant enhancements to its cloud-native database services, including improved multi-region replication and automated scaling capabilities. The enhancements enable organizations to deploy globally distributed applications with consistent performance and high availability.

In May 2026, Microsoft introduced new cloud-native database capabilities within its Azure platform, including integrated vector search for AI applications and enhanced distributed SQL features. The updates enable organizations to build and scale modern applications on cloud-native database services.

Database Types Covered:

  • Relational Database
  • NoSQL Database
  • Distributed SQL Database
  • Time Series Database
  • Multi-Model Database
  • In-Memory Database

Deployment Models Covered:

  • Public Cloud
  • Private Cloud
  • Hybrid Cloud
  • Multi-Cloud

Service Models Covered:

  • Fully Managed Database
  • Self-Managed Database

Workloads Covered:

  • Transactional Processing (OLTP)
  • Analytical Processing (OLAP)
  • Hybrid Transactional/Analytical Processing (HTAP)
  • Real-Time Analytics
  • AI & Machine Learning Workloads

Applications Covered:

  • Web & Mobile Applications
  • Enterprise Applications
  • E-commerce Platforms
  • Internet of Things (IoT)
  • Financial Services
  • Customer Analytics
  • DevOps & CI/CD
  • Gaming

End Users Covered:

  • Banking, Financial Services & Insurance (BFSI)
  • Information Technology & Telecommunications
  • Retail & E-commerce
  • Healthcare & Life Sciences
  • Manufacturing
  • Government & Public Sector
  • Media & Entertainment
  • Energy & Utilities
  • Education

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global Cloud-Native Database Market, By Database Type

  • 5.1 Relational Database
  • 5.2 NoSQL Database
    • 5.2.1 Document Database
    • 5.2.2 Key-Value Database
    • 5.2.3 Wide-Column Database
    • 5.2.4 Graph Database
  • 5.3 Distributed SQL Database
  • 5.4 Time Series Database
  • 5.5 Multi-Model Database
  • 5.6 In-Memory Database

6 Global Cloud-Native Database Market, By Deployment Model

  • 6.1 Public Cloud
  • 6.2 Private Cloud
  • 6.3 Hybrid Cloud
  • 6.4 Multi-Cloud

7 Global Cloud-Native Database Market, By Service Model

  • 7.1 Fully Managed Database
  • 7.2 Self-Managed Database

8 Global Cloud-Native Database Market, By Workload

  • 8.1 Transactional Processing (OLTP)
  • 8.2 Analytical Processing (OLAP)
  • 8.3 Hybrid Transactional/Analytical Processing (HTAP)
  • 8.4 Real-Time Analytics
  • 8.5 AI & Machine Learning Workloads

9 Global Cloud-Native Database Market, By Application

  • 9.1 Web & Mobile Applications
  • 9.2 Enterprise Applications
  • 9.3 E-commerce Platforms
  • 9.4 Internet of Things (IoT)
  • 9.5 Financial Services
  • 9.6 Customer Analytics
  • 9.7 DevOps & CI/CD
  • 9.8 Gaming

10 Global Cloud-Native Database Market, By End User

  • 10.1 Banking, Financial Services & Insurance (BFSI)
  • 10.2 Information Technology & Telecommunications
  • 10.3 Retail & E-commerce
  • 10.4 Healthcare & Life Sciences
  • 10.5 Manufacturing
  • 10.6 Government & Public Sector
  • 10.7 Media & Entertainment
  • 10.8 Energy & Utilities
  • 10.9 Education

11 Global Cloud-Native Database Market, By Geography

  • 11.1 North America
    • 11.1.1 United States
    • 11.1.2 Canada
    • 11.1.3 Mexico
  • 11.2 Europe
    • 11.2.1 United Kingdom
    • 11.2.2 Germany
    • 11.2.3 France
    • 11.2.4 Italy
    • 11.2.5 Spain
    • 11.2.6 Netherlands
    • 11.2.7 Belgium
    • 11.2.8 Sweden
    • 11.2.9 Switzerland
    • 11.2.10 Poland
    • 11.2.11 Rest of Europe
  • 11.3 Asia Pacific
    • 11.3.1 China
    • 11.3.2 Japan
    • 11.3.3 India
    • 11.3.4 South Korea
    • 11.3.5 Australia
    • 11.3.6 Indonesia
    • 11.3.7 Thailand
    • 11.3.8 Malaysia
    • 11.3.9 Singapore
    • 11.3.10 Vietnam
    • 11.3.11 Rest of Asia Pacific
  • 11.4 South America
    • 11.4.1 Brazil
    • 11.4.2 Argentina
    • 11.4.3 Colombia
    • 11.4.4 Chile
    • 11.4.5 Peru
    • 11.4.6 Rest of South America
  • 11.5 Rest of the World (RoW)
    • 11.5.1 Middle East
      • 11.5.1.1 Saudi Arabia
      • 11.5.1.2 United Arab Emirates
      • 11.5.1.3 Qatar
      • 11.5.1.4 Israel
      • 11.5.1.5 Rest of Middle East
    • 11.5.2 Africa
      • 11.5.2.1 South Africa
      • 11.5.2.2 Egypt
      • 11.5.2.3 Morocco
      • 11.5.2.4 Rest of Africa

12 Strategic Market Intelligence

  • 12.1 Industry Value Network and Supply Chain Assessment
  • 12.2 White-Space and Opportunity Mapping
  • 12.3 Product Evolution and Market Life Cycle Analysis
  • 12.4 Channel, Distributor, and Go-to-Market Assessment

13 Industry Developments and Strategic Initiatives

  • 13.1 Mergers and Acquisitions
  • 13.2 Partnerships, Alliances, and Joint Ventures
  • 13.3 New Product Launches and Certifications
  • 13.4 Capacity Expansion and Investments
  • 13.5 Other Strategic Initiatives

14 Company Profiles

  • 14.1 Amazon Web Services (AWS)
  • 14.2 Microsoft
  • 14.3 Google
  • 14.4 Oracle
  • 14.5 IBM
  • 14.6 SAP
  • 14.7 MongoDB
  • 14.8 Cockroach Labs
  • 14.9 Yugabyte
  • 14.10 SingleStore
  • 14.11 Snowflake
  • 14.12 Couchbase
  • 14.13 DataStax
  • 14.14 Redis
  • 14.15 PingCAP

List of Tables

  • Table 1 Global Cloud-Native Database Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global Cloud-Native Database Market Outlook, By Database Type (2023-2034) ($MN)
  • Table 3 Global Cloud-Native Database Market Outlook, By Relational Database (2023-2034) ($MN)
  • Table 4 Global Cloud-Native Database Market Outlook, By NoSQL Database (2023-2034) ($MN)
  • Table 5 Global Cloud-Native Database Market Outlook, By Document Database (2023-2034) ($MN)
  • Table 6 Global Cloud-Native Database Market Outlook, By Key-Value Database (2023-2034) ($MN)
  • Table 7 Global Cloud-Native Database Market Outlook, By Wide-Column Database (2023-2034) ($MN)
  • Table 8 Global Cloud-Native Database Market Outlook, By Graph Database (2023-2034) ($MN)
  • Table 9 Global Cloud-Native Database Market Outlook, By Distributed SQL Database (2023-2034) ($MN)
  • Table 10 Global Cloud-Native Database Market Outlook, By Time Series Database (2023-2034) ($MN)
  • Table 11 Global Cloud-Native Database Market Outlook, By Multi-Model Database (2023-2034) ($MN)
  • Table 12 Global Cloud-Native Database Market Outlook, By In-Memory Database (2023-2034) ($MN)
  • Table 13 Global Cloud-Native Database Market Outlook, By Deployment Model (2023-2034) ($MN)
  • Table 14 Global Cloud-Native Database Market Outlook, By Public Cloud (2023-2034) ($MN)
  • Table 15 Global Cloud-Native Database Market Outlook, By Private Cloud (2023-2034) ($MN)
  • Table 16 Global Cloud-Native Database Market Outlook, By Hybrid Cloud (2023-2034) ($MN)
  • Table 17 Global Cloud-Native Database Market Outlook, By Multi-Cloud (2023-2034) ($MN)
  • Table 18 Global Cloud-Native Database Market Outlook, By Service Model (2023-2034) ($MN)
  • Table 19 Global Cloud-Native Database Market Outlook, By Fully Managed Database (2023-2034) ($MN)
  • Table 20 Global Cloud-Native Database Market Outlook, By Self-Managed Database (2023-2034) ($MN)
  • Table 21 Global Cloud-Native Database Market Outlook, By Workload (2023-2034) ($MN)
  • Table 22 Global Cloud-Native Database Market Outlook, By Transactional Processing (OLTP) (2023-2034) ($MN)
  • Table 23 Global Cloud-Native Database Market Outlook, By Analytical Processing (OLAP) (2023-2034) ($MN)
  • Table 24 Global Cloud-Native Database Market Outlook, By Hybrid Transactional/Analytical Processing (HTAP) (2023-2034) ($MN)
  • Table 25 Global Cloud-Native Database Market Outlook, By Real-Time Analytics (2023-2034) ($MN)
  • Table 26 Global Cloud-Native Database Market Outlook, By AI & Machine Learning Workloads (2023-2034) ($MN)
  • Table 27 Global Cloud-Native Database Market Outlook, By Application (2023-2034) ($MN)
  • Table 28 Global Cloud-Native Database Market Outlook, By Web & Mobile Applications (2023-2034) ($MN)
  • Table 29 Global Cloud-Native Database Market Outlook, By Enterprise Applications (2023-2034) ($MN)
  • Table 30 Global Cloud-Native Database Market Outlook, By E-commerce Platforms (2023-2034) ($MN)
  • Table 31 Global Cloud-Native Database Market Outlook, By Internet of Things (IoT) (2023-2034) ($MN)
  • Table 32 Global Cloud-Native Database Market Outlook, By Financial Services (2023-2034) ($MN)
  • Table 33 Global Cloud-Native Database Market Outlook, By Customer Analytics (2023-2034) ($MN)
  • Table 34 Global Cloud-Native Database Market Outlook, By DevOps & CI/CD (2023-2034) ($MN)
  • Table 35 Global Cloud-Native Database Market Outlook, By Gaming (2023-2034) ($MN)
  • Table 36 Global Cloud-Native Database Market Outlook, By End User (2023-2034) ($MN)
  • Table 37 Global Cloud-Native Database Market Outlook, By Banking, Financial Services & Insurance (BFSI) (2023-2034) ($MN)
  • Table 38 Global Cloud-Native Database Market Outlook, By Information Technology & Telecommunications (2023-2034) ($MN)
  • Table 39 Global Cloud-Native Database Market Outlook, By Retail & E-commerce (2023-2034) ($MN)
  • Table 40 Global Cloud-Native Database Market Outlook, By Healthcare & Life Sciences (2023-2034) ($MN)
  • Table 41 Global Cloud-Native Database Market Outlook, By Manufacturing (2023-2034) ($MN)
  • Table 42 Global Cloud-Native Database Market Outlook, By Government & Public Sector (2023-2034) ($MN)
  • Table 43 Global Cloud-Native Database Market Outlook, By Media & Entertainment (2023-2034) ($MN)
  • Table 44 Global Cloud-Native Database Market Outlook, By Energy & Utilities (2023-2034) ($MN)
  • Table 45 Global Cloud-Native Database Market Outlook, By Education (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.