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市场调查报告书
商品编码
1889198

全球自治资料库市场：预测至 2032 年－按组件、部署方式、组织规模、功能集、用例、最终用户和地区进行分析

Autonomous Database Market Forecasts to 2032 - Global Analysis By Component (Solution and Services), Deployment Mode, Organization Size, Feature Set, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的一项研究，预计到 2025 年，全球自治资料库市场价值将达到 21.6 亿美元，到 2032 年将达到 74.1 亿美元，在预测期内的复合年增长率为 19.2%。

自治资料库是一种智慧资料平台，它利用自动化和人工智慧技术进行自我管理、保护和维护。它透过自动执行配置、最佳化、更新、备份和资源扩展等任务来简化操作。透过减少人工干预，它提高了系统的可靠性、性能和灾难復原能力。企业正在采用自治资料库来减轻营运负担、提高效率并及时获取洞察，从而帮助他们应对现代资料密集型工作负载和应用程式。

对即时洞察的需求

自主资料库能够实现持续监控和自动优化，确保无需人工干预即可获得洞察。随着各行业采用人工智慧驱动的工作流程，对即时分析的需求变得愈发迫切。企业正在利用自主系统处理来自物联网感测器、客户互动和数位平台的串流数据。这种转变有助于实现主动营运、预测智慧和提升客户体验。因此，对即时资料可见性的追求正在加速自主资料库解决方案的普及。

数据品质问题

结构不良、不一致或不完整的资料会降低自动化流程的准确性。即使是先进的人工智慧驱动系统，如果底层资料不可信，也难以发挥最佳效能。企业在整合旧有系统时常常面临挑战，容易引入不一致和错误。这些问题促使人们需要额外的检验工具和资料管治框架。因此，对资料品质的担忧持续阻碍自治资料库的全面普及。

云端原生采用

企业正将工作负载迁移到云端，以获得可扩展性、柔软性和降低基础设施成本等优势。自治资料库可与云端环境无缝集成，并支援自我调优、自我修復和自动更新。随着混合云和多重云端策略的兴起，各组织正在考虑采用自治系统来提高营运效率。数位转型计画的兴起正推动企业对其资料架构进行现代化改造。这种向云原生生态系统的转变显着拓展了市场的成长前景。

资料隐私和安全漏洞

随着资料库自动化程度的提高，针对配置错误和漏洞的网路攻击也可能随之增加。储存在云端环境中的敏感资料尤其容易受到未授权存取。诸如GDPR和CCPA等法规结构进一步加剧了合规性的挑战。资料外洩可能会削弱人们对自主系统的信任，并阻碍其在风险规避型产业中的应用。因此，持续存在的网路安全风险对市场扩张构成了重大障碍。

新冠疫情的感染疾病：

新冠疫情加速了数位化基础设施和自动化数据系统的转型。各组织机构纷纷采用自主资料库来支援远端营运并维持业务永续营运。这一转变导致供应链、医疗保健和客户参与流程对即时分析的依赖显着增强。然而，疫情初期的一些干扰延缓了实施进度，并影响了IT支出。最终，疫情反而强化了市场成长动能。

在预测期内，解决方案细分市场将占据最大的市场份额。

由于对自管理资料库平台的需求不断增长，预计在预测期内，解决方案领域将占据最大的市场份额。这些解决方案提供自动化的效能调优、备份、修补程式和安全控制。企业更倾向于选择能够减少人工干预并提高可靠性的整合解决方案。人工智慧和机器学习的进步正使自主资料库解决方案变得更加智慧。企业正在部署这些系统，以支援大规模分析、关键任务工作负载和云端迁移策略。

在预测期内，医疗保健和生命科学产业的复合年增长率将最高。

在预测期内，医疗保健和生命科学领域预计将保持最高的成长率，这主要得益于对高效数据管理日益增长的需求。自主资料库有助于即时临床分析、病患监测和研究数据处理。远端医疗和数位健康平台的兴起进一步推动了对自动化数据解决方案的需求。人工智慧技术能够实现更快速的诊断、预测分析和个人化治疗。严格的监管要求正在推动安全合规的自主资料库系统的应用。

占比最大的地区：

由于北美拥有强大的技术基础设施和较高的云端采用率，预计该地区将在预测期内占据最大的市场份额。该地区的主要企业是人工智慧驱动资料库系统的早期采用者。主要技术提供者的存在正在加速创新和应用。金融、医疗保健和零售等高度依赖即时分析的行业正在推动市场成长。政府支持数位转型的措施进一步增强了该地区的需求。

年复合成长率最高的地区：

由于新兴经济体数位化的快速推进，预计亚太地区在预测期内将呈现最高的复合年增长率。该地区的企业正在采用云端基础的系统来实现其IT营运的现代化。对人工智慧、自动化和高阶分析领域不断增长的投资正在推动自主资料库的普及。电子商务、银行、金融和保险（BFSI）以及通讯等产业对即时数据平台的使用日益增加。政府主导的智慧基础设施计划正在进一步加速市场应用。

免费客製化服务：

订阅本报告的用户可从以下免费自订选项中选择一项：

  • 公司简介
    • 对最多三家其他公司进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域分类
    • 根据客户兴趣对主要国家进行市场估算、预测和复合年增长率分析（註：基于可行性检查）
  • 竞争基准化分析
    • 基于产品系列、地域覆盖和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 引言

  • 概述
  • 相关利益者
  • 分析范围
  • 分析方法
  • 分析材料

第三章 市场趋势分析

  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代产品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球自主资料库市场（按组件划分）

  • 解决方案
  • 服务
    • 专业服务
    • 託管服务

6. 全球自治资料库市场依部署方式划分

  • 公共云端
  • 私有云端
  • 混合云端

7. 按组织规模分類的全球自治资料库市场

  • 大公司
  • 中小企业

8. 全球自治资料库市场（依功能集划分）

  • 自动驾驶
    • 自动配置
    • 自动缩放
  • 自卫
    • 自动修补
    • 威胁侦测
  • 自癒
    • 自动恢復
    • 故障检测
  • 自主性能优化
  • 自动化备份生命週期管理

9. 全球自治资料库市场（按应用划分）

  • 资料仓储
  • 分析与报告
  • 事务处理（OLTP）
  • 备份和灾害復原
  • 财务规划与会计
  • 资产和库存管理
  • 客户体验与客户关係管理
  • 诈欺侦测和风险管理

10. 全球自治资料库市场（以最终用户划分）

  • 云端服务供应商
  • 公司
  • 数据分析公司
  • IT服务和託管服务供应商
  • 其他最终用户

11. 全球自治资料库市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美国家
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十二章：主要趋势

  • 合约、商业伙伴关係和合资企业
  • 企业合併（M&A）
  • 新产品上市
  • 业务拓展
  • 其他关键策略

第十三章：企业概况

  • Oracle Corporation
  • Amazon Web Services, Inc.
  • Microsoft Corporation
  • Google LLC
  • IBM Corporation
  • Snowflake Inc.
  • Teradata Corporation
  • Databricks, Inc.
  • SAP SE
  • Alibaba Cloud
  • Huawei Technologies Co., Ltd.
  • MongoDB, Inc.
  • Cockroach Labs, Inc.
  • Couchbase, Inc.
  • DataStax, Inc.
Product Code: SMRC32658

According to Stratistics MRC, the Global Autonomous Database Market is accounted for $2.16 billion in 2025 and is expected to reach $7.41 billion by 2032 growing at a CAGR of 19.2% during the forecast period. An autonomous database refers to an intelligent data platform that independently manages, secures, and maintains itself using automation and AI technologies. It streamlines operations by automatically executing activities like setup, optimization, updating, backup, and resource scaling. By reducing the need for manual involvement, it improves system reliability, performance, and protection against failures. Businesses adopt autonomous databases to cut operational effort, boost efficiency, and gain timely insights, making it valuable for handling modern, data-intensive workloads and applications.

Market Dynamics:

Driver:

Need for real-time insights

Autonomous databases enable continuous monitoring and automated optimization, ensuring insights are delivered without manual intervention. As industries adopt AI-driven workflows, the need for instant analytics becomes even more crucial. Businesses are leveraging autonomous systems to handle streaming data from IoT sensors, customer interactions, and digital platforms. This shift supports proactive operations, predictive intelligence, and improved customer experiences. Consequently, the push for real-time data visibility is accelerating the adoption of autonomous database solutions.

Restraint:

Data quality issues

Poorly structured, inconsistent, or incomplete data reduces the accuracy of automated processes. Even advanced AI-driven systems struggle to perform optimally when underlying data is unreliable. Organizations often face challenges in integrating legacy systems, leading to discrepancies and errors. These issues increase the need for additional validation tools and data governance frameworks. As a result, data quality concerns continue to slow down the full-scale deployment of autonomous databases.

Opportunity:

Cloud-native adoption

Businesses are migrating workloads to the cloud to benefit from scalability, flexibility, and reduced infrastructure overhead. Autonomous databases integrate seamlessly with cloud environments, enabling self-tuning, self-healing, and automated updates. As hybrid and multi-cloud strategies gain momentum, organizations are exploring autonomous systems for improved operational efficiency. The rise of digital transformation initiatives is pushing enterprises to modernize data architectures. This shift toward cloud-native ecosystems greatly expands market growth prospects.

Threat:

Data privacy and security breaches

As databases become more automated, cyberattacks targeting misconfigurations or vulnerabilities can increase. Sensitive data stored in cloud environments is particularly exposed to unauthorized access. Regulatory frameworks like GDPR and CCPA further heighten compliance challenges. Breaches can undermine trust in autonomous systems, discouraging adoption among risk-averse industries. Thus, ongoing cybersecurity risks create significant hurdles for market expansion.

Covid-19 Impact:

The Covid-19 pandemic accelerated the shift toward digital infrastructure and automated data systems. Organizations adopted autonomous databases to support remote operations and maintain business continuity. This transition increased reliance on real-time analytics for supply chain, healthcare, and customer engagement processes. However, initial disruptions slowed implementation timelines and impacted IT spending. As a result, the pandemic ultimately strengthened the market's growth trajectory.

The solution segment is expected to be the largest during the forecast period

The solution segment is expected to account for the largest market share during the forecast period, due to increasing demand for self-managing database platforms. These solutions offer automated performance tuning, backup, patching, and security controls. Organizations prefer integrated offerings that reduce manual workload and improve reliability. Advancements in AI and machine learning are enhancing the intelligence of autonomous database solutions. Enterprises are adopting these systems to support large-scale analytics, mission-critical workloads, and cloud migration strategies.

The healthcare and life sciences segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the healthcare and life sciences segment is predicted to witness the highest growth rate, due to growing needs for efficient data management. Autonomous databases support real-time clinical analysis, patient monitoring, and research data processing. The rise of telemedicine and digital health platforms further increases the demand for automated data solutions. AI-powered capabilities enable faster diagnosis, predictive analytics, and treatment personalization. Strict regulatory requirements drive adoption of secure, compliant, and self-governing database systems.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to strong technological infrastructure and high cloud adoption. Major enterprises in the region are early adopters of AI-driven database systems. The presence of key technology providers accelerates innovation and deployment. Industries such as finance, healthcare, and retail rely heavily on real-time analytics, boosting market growth. Government initiatives supporting digital transformation further strengthen regional demand.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, owing to rapid digitization across emerging economies. Organizations in the region are adopting cloud-based systems to modernize IT operations. Growing investments in AI, automation, and advanced analytics are propelling autonomous database adoption. Industries such as e-commerce, BFSI, and telecom are expanding their use of real-time data platforms. Government-led smart infrastructure projects further accelerate market uptake.

Key players in the market

Some of the key players in Autonomous Database Market include Oracle Corp, Amazon W, Microsoft, Google LLC, IBM Corp, Snowflake, Teradata C, Databricks, SAP SE, Alibaba Cl, Huawei Te, MongoDB, Cockroach, Couchbase, and DataStax.

Key Developments:

In November 2025, IBM and the University of Dayton announced an agreement for the joint research and development of next-generation semiconductor technologies and materials. The collaboration aims to advance critical technologies for the age of AI including AI hardware, advanced packaging, and photonics.

In October 2025, Oracle announced collaboration with Microsoft to develop an integration blueprint to help manufacturers improve supply chain efficiency and responsiveness. The blueprint will enable organizations using Oracle Fusion Cloud Supply Chain & Manufacturing (SCM) to improve data-driven decision making and automate key supply chain processes by capturing live insights from factory equipment and sensors through Azure IoT Operations and Microsoft Fabric.

Components Covered:

  • Solution
  • Services

Deployment Modes Covered:

  • Public Cloud
  • Private Cloud
  • Hybrid Cloud

Organization Sizes Covered:

  • Large Enterprises
  • Small & Medium Enterprises (SMEs)

Feature Sets Covered:

  • Self-Driving
  • Self-Securing
  • Self-Repairing
  • Autonomous Performance Optimization
  • Automated Backup & Lifecycle Management

Applications Covered:

  • Data Warehousing
  • Analytics & Reporting
  • Transaction Processing (OLTP)
  • Backup & Disaster Recovery
  • Financial Planning & Accounting
  • Asset & Inventory Management
  • Customer Experience & CRM
  • Fraud Detection & Risk Management

End Users Covered:

  • Cloud Service Providers
  • Enterprises
  • Data Analytics Companies
  • IT Service & Managed Service Providers
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & 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 2024, 2025, 2026, 2028, and 2032
  • 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

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Autonomous Database Market, By Component

  • 5.1 Introduction
  • 5.2 Solution
  • 5.3 Services
    • 5.3.1 Professional Services
    • 5.3.2 Managed Services

6 Global Autonomous Database Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 Public Cloud
  • 6.3 Private Cloud
  • 6.4 Hybrid Cloud

7 Global Autonomous Database Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Large Enterprises
  • 7.3 Small & Medium Enterprises (SMEs)

8 Global Autonomous Database Market, By Feature Set

  • 8.1 Introduction
  • 8.2 Self-Driving
    • 8.2.1 Automated provisioning
    • 8.2.2 Auto-scaling
  • 8.3 Self-Securing
    • 8.3.1 Automated patching
    • 8.3.2 Threat detection
  • 8.4 Self-Repairing
    • 8.4.1 Automated recovery
    • 8.4.2 Fault detection
  • 8.5 Autonomous Performance Optimization
  • 8.6 Automated Backup & Lifecycle Management

9 Global Autonomous Database Market, By Application

  • 9.1 Introduction
  • 9.2 Data Warehousing
  • 9.3 Analytics & Reporting
  • 9.4 Transaction Processing (OLTP)
  • 9.5 Backup & Disaster Recovery
  • 9.6 Financial Planning & Accounting
  • 9.7 Asset & Inventory Management
  • 9.8 Customer Experience & CRM
  • 9.9 Fraud Detection & Risk Management

10 Global Autonomous Database Market, By End User

  • 10.1 Introduction
  • 10.2 Cloud Service Providers
  • 10.3 Enterprises
  • 10.4 Data Analytics Companies
  • 10.5 IT Service & Managed Service Providers
  • 10.6 Other End Users

11 Global Autonomous Database Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Oracle Corporation
  • 13.2 Amazon Web Services, Inc.
  • 13.3 Microsoft Corporation
  • 13.4 Google LLC
  • 13.5 IBM Corporation
  • 13.6 Snowflake Inc.
  • 13.7 Teradata Corporation
  • 13.8 Databricks, Inc.
  • 13.9 SAP SE
  • 13.10 Alibaba Cloud
  • 13.11 Huawei Technologies Co., Ltd.
  • 13.12 MongoDB, Inc.
  • 13.13 Cockroach Labs, Inc.
  • 13.14 Couchbase, Inc.
  • 13.15 DataStax, Inc.

List of Tables

  • Table 1 Global Autonomous Database Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Autonomous Database Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Autonomous Database Market Outlook, By Solution (2024-2032) ($MN)
  • Table 4 Global Autonomous Database Market Outlook, By Services (2024-2032) ($MN)
  • Table 5 Global Autonomous Database Market Outlook, By Professional Services (2024-2032) ($MN)
  • Table 6 Global Autonomous Database Market Outlook, By Managed Services (2024-2032) ($MN)
  • Table 7 Global Autonomous Database Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 8 Global Autonomous Database Market Outlook, By Public Cloud (2024-2032) ($MN)
  • Table 9 Global Autonomous Database Market Outlook, By Private Cloud (2024-2032) ($MN)
  • Table 10 Global Autonomous Database Market Outlook, By Hybrid Cloud (2024-2032) ($MN)
  • Table 11 Global Autonomous Database Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 12 Global Autonomous Database Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 13 Global Autonomous Database Market Outlook, By Small & Medium Enterprises (SMEs) (2024-2032) ($MN)
  • Table 14 Global Autonomous Database Market Outlook, By Feature Set (2024-2032) ($MN)
  • Table 15 Global Autonomous Database Market Outlook, By Self-Driving (2024-2032) ($MN)
  • Table 16 Global Autonomous Database Market Outlook, By Automated provisioning (2024-2032) ($MN)
  • Table 17 Global Autonomous Database Market Outlook, By Auto-scaling (2024-2032) ($MN)
  • Table 18 Global Autonomous Database Market Outlook, By Self-Securing (2024-2032) ($MN)
  • Table 19 Global Autonomous Database Market Outlook, By Automated patching (2024-2032) ($MN)
  • Table 20 Global Autonomous Database Market Outlook, By Threat detection (2024-2032) ($MN)
  • Table 21 Global Autonomous Database Market Outlook, By Self-Repairing (2024-2032) ($MN)
  • Table 22 Global Autonomous Database Market Outlook, By Automated recovery (2024-2032) ($MN)
  • Table 23 Global Autonomous Database Market Outlook, By Fault detection (2024-2032) ($MN)
  • Table 24 Global Autonomous Database Market Outlook, By Autonomous Performance Optimization (2024-2032) ($MN)
  • Table 25 Global Autonomous Database Market Outlook, By Automated Backup & Lifecycle Management (2024-2032) ($MN)
  • Table 26 Global Autonomous Database Market Outlook, By Application (2024-2032) ($MN)
  • Table 27 Global Autonomous Database Market Outlook, By Data Warehousing (2024-2032) ($MN)
  • Table 28 Global Autonomous Database Market Outlook, By Analytics & Reporting (2024-2032) ($MN)
  • Table 29 Global Autonomous Database Market Outlook, By Transaction Processing (OLTP) (2024-2032) ($MN)
  • Table 30 Global Autonomous Database Market Outlook, By Backup & Disaster Recovery (2024-2032) ($MN)
  • Table 31 Global Autonomous Database Market Outlook, By Financial Planning & Accounting (2024-2032) ($MN)
  • Table 32 Global Autonomous Database Market Outlook, By Asset & Inventory Management (2024-2032) ($MN)
  • Table 33 Global Autonomous Database Market Outlook, By Customer Experience & CRM (2024-2032) ($MN)
  • Table 34 Global Autonomous Database Market Outlook, By Fraud Detection & Risk Management (2024-2032) ($MN)
  • Table 35 Global Autonomous Database Market Outlook, By End User (2024-2032) ($MN)
  • Table 36 Global Autonomous Database Market Outlook, By Cloud Service Providers (2024-2032) ($MN)
  • Table 37 Global Autonomous Database Market Outlook, By Enterprises (2024-2032) ($MN)
  • Table 38 Global Autonomous Database Market Outlook, By Data Analytics Companies (2024-2032) ($MN)
  • Table 39 Global Autonomous Database Market Outlook, By IT Service & Managed Service Providers (2024-2032) ($MN)
  • Table 40 Global Autonomous Database Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.