RDB(Relational Database) 시장 : 세계 산업 규모, 점유율, 동향, 기회, 예측 - 유형별, 배포별, 최종사용자별, 지역별, 경쟁(2021-2031년)

The Global Relational Database Market is projected to expand significantly, rising from USD 69.22 Billion in 2025 to USD 142.36 Billion by 2031, reflecting a CAGR of 12.77%. Relational databases function as digital repositories that structure information into predefined tables featuring rows and columns, establishing logical connections between data points. This market trajectory is primarily driven by the exponential growth of enterprise data and the indispensable need for reliable transactional consistency within financial and operational systems. Furthermore, sustained demand for structured data management in core business applications continues to support growth by ensuring data integrity and accuracy. Highlighting the enduring industrial reliance on these foundational technologies, the IEEE reported in 2024 that SQL maintained the top position in job market rankings.

Despite this robust expansion, the market faces a significant challenge that could hinder growth. Relational systems often encounter inherent limitations regarding horizontal scalability, particularly when processing massive volumes of unstructured information. These technical constraints make it difficult to accommodate the variety and velocity of modern big data workloads without incurring substantial financial and performance costs when compared to more flexible alternative architectures.

Market Driver

The surging adoption of cloud-based database services and Database-as-a-Service (DBaaS) models is fundamentally reshaping the market as enterprises migrate from on-premises infrastructure to achieve greater agility and cost-efficiency. Organizations are increasingly utilizing fully managed platforms to offload administrative burdens such as patching, scaling, and backups, which allows technical teams to focus on innovation rather than maintenance. This migration trend is quantified by industry data highlighting a rapid operational shift toward flexible environments. According to Redgate's "State of the Database Landscape 2024" report released in February 2024, the percentage of organizations hosting their databases mostly or fully in the cloud rose to 36% in 2023, reflecting a definitive move away from traditional data centers.

Simultaneously, the market is being propelled by heightened demand for real-time data analytics and business intelligence, necessitating databases capable of supporting high-velocity transaction processing and complex analytical queries. Modern applications now require immediate insights derived from massive datasets, pushing relational systems to integrate deeper support for AI and machine learning workflows. As noted by Google Cloud in their "2024 Data and AI Trends Report" from April 2024, 84% of data leaders believe generative AI will help their organization reduce time-to-insight, underscoring the critical role of data platforms in enabling rapid decision-making. This evolution is also influencing technology choices; according to Stack Overflow in 2024, PostgreSQL emerged as the preferred choice for 49% of developers, indicating a broader market preference for robust, open-standard systems capable of handling these advanced analytical requirements.

Market Challenge

The rigid architecture of relational databases regarding horizontal scalability presents a substantial hurdle to market expansion. As enterprises ingest massive volumes of unstructured information, such as sensor logs and social media feeds, the fixed table-based structure of these systems struggles to distribute workloads efficiently across multiple servers. This limitation forces organizations to rely on expensive vertical scaling methods or complex modifications to maintain performance, which frequently leads to increased latency and operational costs. Consequently, the inability to natively accommodate the velocity and variety of modern big data streams creates a technical ceiling that restricts the adoption of relational systems for high-growth, data-intensive applications.

This constraint directly impacts market momentum by diverting investment toward more flexible non-relational architectures. When businesses face the financial and technical burden of forcing dynamic data into structured schemas, they increasingly opt for alternative solutions that offer superior elasticity. This trend is evident in developer preferences for tools that bypass these specific limitations. According to Stack Overflow in 2024, approximately 25 percent of professional developers reported utilizing MongoDB, a document-oriented database, indicating a measurable portion of the industrial workload is shifting away from relational models to manage unstructured data requirements. This migration demonstrates how scalability challenges effectively cap the potential market share of relational databases in the expanding sector of big data management.

Market Trends

The integration of vector search capabilities for generative AI is expanding the utility of relational engines by allowing them to natively query high-dimensional embeddings. This convergence enables enterprises to support retrieval-augmented generation workflows without the architectural complexity of maintaining separate, specialized vector stores. By embedding these features directly into the core database, organizations can ensure transactional consistency while powering modern machine learning applications. This consolidation trend is substantiated by recent industrial data; according to Retool's "State of AI 2024" report from June 2024, vector database utilization surged to 63.6% in 2024, with the relational extension pgvector securing 21.3% of respondent preference, effectively rivaling purpose-built niche competitors.

The rise of distributed SQL and NewSQL architectures is addressing the critical market need for systems that combine horizontal elasticity with strict transactional guarantees. Unlike legacy monolithic databases that often suffer from downtime during scaling events, these modern architectures automatically distribute data across multiple nodes and geographies to ensure continuous availability. This resilience has become a primary selection criterion for global enterprises facing the financial risks of service interruptions. The urgency of this shift is highlighted by operational realities noted by Cockroach Labs in the "State of Resilience 2025" report from October 2024, where 100% of technology executives reported experiencing revenue losses due to outages in the past year, underscoring the imperative for the fault-tolerant design that distributed SQL provides.

Key Market Players

• Oracle Corporation
• Microsoft Corporation
• IBM Corporation
• Google LLC
• SAP SE
• MongoDB, Inc.
• Huawei Technologies Co., Ltd.
• Amazon.com, Inc.
• Rackspace Technology, Inc.
• Snowflake Inc.

Report Scope

In this report, the Global Relational Database Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Relational Database Market, By Type

• In-memory
• Disk-based
• Others

Relational Database Market, By Deployment

• Cloud-based
• On-premises

Relational Database Market, By End User

• BFSI
• IT & Telecom
• Retail & E-commerce
• Manufacturing
• Healthcare
• Others

Relational Database Market, By Region

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
• South America
  • Brazil
  • Argentina
  • Colombia
• Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Relational Database Market.

Available Customizations:

Global Relational Database Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Relational Database Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Type (In-memory, Disk-based, Others)
  • 5.2.2. By Deployment (Cloud-based, On-premises)
  • 5.2.3. By End User (BFSI, IT & Telecom, Retail & E-commerce, Manufacturing, Healthcare, Others)
  • 5.2.4. By Region
  • 5.2.5. By Company (2025)
• 5.3. Market Map

6. North America Relational Database Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Type
  • 6.2.2. By Deployment
  • 6.2.3. By End User
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States Relational Database Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Type
      • 6.3.1.2.2. By Deployment
      • 6.3.1.2.3. By End User
  • 6.3.2. Canada Relational Database Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Type
      • 6.3.2.2.2. By Deployment
      • 6.3.2.2.3. By End User
  • 6.3.3. Mexico Relational Database Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Type
      • 6.3.3.2.2. By Deployment
      • 6.3.3.2.3. By End User

7. Europe Relational Database Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Type
  • 7.2.2. By Deployment
  • 7.2.3. By End User
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany Relational Database Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Type
      • 7.3.1.2.2. By Deployment
      • 7.3.1.2.3. By End User
  • 7.3.2. France Relational Database Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Type
      • 7.3.2.2.2. By Deployment
      • 7.3.2.2.3. By End User
  • 7.3.3. United Kingdom Relational Database Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Type
      • 7.3.3.2.2. By Deployment
      • 7.3.3.2.3. By End User
  • 7.3.4. Italy Relational Database Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Type
      • 7.3.4.2.2. By Deployment
      • 7.3.4.2.3. By End User
  • 7.3.5. Spain Relational Database Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Type
      • 7.3.5.2.2. By Deployment
      • 7.3.5.2.3. By End User

8. Asia Pacific Relational Database Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Type
  • 8.2.2. By Deployment
  • 8.2.3. By End User
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China Relational Database Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Type
      • 8.3.1.2.2. By Deployment
      • 8.3.1.2.3. By End User
  • 8.3.2. India Relational Database Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Type
      • 8.3.2.2.2. By Deployment
      • 8.3.2.2.3. By End User
  • 8.3.3. Japan Relational Database Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Type
      • 8.3.3.2.2. By Deployment
      • 8.3.3.2.3. By End User
  • 8.3.4. South Korea Relational Database Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Type
      • 8.3.4.2.2. By Deployment
      • 8.3.4.2.3. By End User
  • 8.3.5. Australia Relational Database Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Type
      • 8.3.5.2.2. By Deployment
      • 8.3.5.2.3. By End User

9. Middle East & Africa Relational Database Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Type
  • 9.2.2. By Deployment
  • 9.2.3. By End User
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia Relational Database Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Type
      • 9.3.1.2.2. By Deployment
      • 9.3.1.2.3. By End User
  • 9.3.2. UAE Relational Database Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Type
      • 9.3.2.2.2. By Deployment
      • 9.3.2.2.3. By End User
  • 9.3.3. South Africa Relational Database Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Type
      • 9.3.3.2.2. By Deployment
      • 9.3.3.2.3. By End User

10. South America Relational Database Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Type
  • 10.2.2. By Deployment
  • 10.2.3. By End User
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Relational Database Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Type
      • 10.3.1.2.2. By Deployment
      • 10.3.1.2.3. By End User
  • 10.3.2. Colombia Relational Database Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Type
      • 10.3.2.2.2. By Deployment
      • 10.3.2.2.3. By End User
  • 10.3.3. Argentina Relational Database Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Type
      • 10.3.3.2.2. By Deployment
      • 10.3.3.2.3. By End User

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends & Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Global Relational Database Market: SWOT Analysis

14. Porter's Five Forces Analysis

• 14.1. Competition in the Industry
• 14.2. Potential of New Entrants
• 14.3. Power of Suppliers
• 14.4. Power of Customers
• 14.5. Threat of Substitute Products

15. Competitive Landscape

• 15.1. Oracle Corporation
  • 15.1.1. Business Overview
  • 15.1.2. Products & Services
  • 15.1.3. Recent Developments
  • 15.1.4. Key Personnel
  • 15.1.5. SWOT Analysis
• 15.2. Microsoft Corporation
• 15.3. IBM Corporation
• 15.4. Google LLC
• 15.5. SAP SE
• 15.6. MongoDB, Inc.
• 15.7. Huawei Technologies Co., Ltd.
• 15.8. Amazon.com, Inc.
• 15.9. Rackspace Technology, Inc.
• 15.10. Snowflake Inc.

16. Strategic Recommendations

17. About Us & Disclaimer