세계의 서버리스 컴퓨팅 시장 : 서비스 유형별, 서비스 모델별, 전개 모델별, 조직 규모별, 산업별, 지역별 - 예측(-2029년)

The serverless computing market is expected to grow from USD 21.9 billion in 2024 to USD 44.7 billion by 2029 at a Compound Annual Growth Rate (CAGR) of 15.3% during the forecast period. As artificial intelligence (AI) and machine learning integration rise within serverless computing platforms, this increases application development and deployment efficiency. AI-driven tools will automate resource allocation, optimize performance, and monitor applications. This reduces the time and effort needed to manage serverless environments. Machine learning algorithms increase the accuracy and relevance of real-time data processing to enable organizations to make informed decisions and optimize their application outcomes. This automation simplifies the development process, aligns it further with strategic goals, and ensures high-quality results, which drives success across the board for the entire serverless infrastructure.

"As per service type, application integration will grow at the highest CAGR during the forecast period."

Application integration in the serverless computing market involves various services that aim to enable smooth communication between different systems and applications. This covers event-driven services that react to specific events or triggers, allowing for instant processing and automation of workflows; messaging services that manage message exchange between various applications or services, ensuring dependable and asynchronous communication; and API management, which offers tools for creating, deploying, and overseeing APIs that facilitate interaction between applications and third-party services. These integration services are scalable and fully managed, supporting intricate, distributed architectures and streamlining the development of interconnected applications. Companies can simplify processes, improve adaptability, and attain higher productivity within their serverless setups using these services.

"As per the deployment model segment, public cloud will hold the largest share during the forecast period."

Serverless computing relies on the public cloud deployment type, which features a communal infrastructure overseen by third-party cloud service providers like AWS, Microsoft Azure, and Google Cloud Platform. This model provides instant serverless resource access, such as computing power, storage, and services, without requiring organizations to handle physical servers or infrastructure. Public cloud serverless solutions are lauded for their ability to automatically scale according to workload needs and their cost-efficiency, billing users solely for the resources they utilize through a pay-as-you-go pricing structure. Moreover, this deployment strategy takes advantage of the cloud provider's robust security measures, compliance certifications, and numerous global data centers. This enables businesses to quickly and efficiently deploy and expand applications while trusting the provider to manage infrastructure and security.

"As per organization size, the small enterprises will grow with the highest CAGR during the forecast period."

Small businesses are turning to serverless solutions to address the issues linked to traditional infrastructure management. By using serverless computing, these firms can avoid the difficulties and expenses associated with configuring, updating, and expanding physical servers. The pay-as-you-go pricing model allows small businesses to minimize operational costs by paying only for their computing resources, thereby decreasing initial financial commitments. This adaptability allows for quick deployment of applications and will enable companies to adjust the size of their operations as their needs change. Serverless platforms also offer essential functionalities such as automatic scalability and integrated security, which are especially advantageous for small businesses with limited IT resources. These benefits enable small companies to rapidly innovate, present fresh concepts, and efficiently challenge bigger competitors in their sector without the limitations of conventional infrastructure.

The breakup of the profiles of the primary participants is below:

• By Company: Tier I: 10%, Tier II: 25%, and Tier III: 65%
• By Designation: C-Level Executives: 25%, Director Level: 50%, and Others: 25%
• By Region: North America: 40%, Europe: 30%, Asia Pacific: 20%, Rest of World: 10%

Note: Others include sales managers, marketing managers, and product managers

Note: The rest of the World consists of the Middle East & Africa, and Latin America

Note: Tier 1 companies have revenues of more than USD 100 million; tier 2 companies' revenue ranges from USD 10 million to USD 100 million; and tier 3 companies' revenue is less than 10 million

Source: Secondary Literature, Expert Interviews, and MarketsandMarkets Analysis

Major companies offering serverless computing solutions and services are AWS (US), Microsoft (US), Google (US), IBM (US), Oracle (US), Alibaba Cloud (China), Tencent Cloud (China), DigitalOcean (US), Twilio (US), Cloudflare (US), MongoDB (US).

Research coverage:

In this study, an in-depth analysis of the Serverless Computing market is done based on market trends, potential growth during 2019, and a forecast up to 2024-2029. Further, it gives detailed market trends, a competitive landscape, market size, forecasts, and key players' analysis of the Serverless Computing market. This market study analyzes the growth rate and penetration of Serverless Computing across all the major regions.

Reasons to buy this report:

The report will aid the market leaders/new entrants in the following: Details regarding the closest approximations of the revenue numbers for the serverless computing market and its subsegments. This study will aid the stakeholders in understanding the competitive landscape; it gives more insights to position their businesses better and plan suitable go-to-market strategies. It also helps the stakeholders understand the market pulse and provides information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

• Analysis of critical drivers (Increasing technological advancements, ongoing innovation in development tools and frameworks, future of microservices lies in serverless and function-as-a-service, increasing number of verticals utilizing distributed workloads, shift from DevOps to serverless computing), restraints (Loss of control over the infrastructure, risk of vendor lock-in), opportunities (Microservice-based deployment, serverless backends in mobile and web development, increasing number of verticals utilizing distributed workloads), and challenges (Issues with third-party services, architectural and operational complexity, cost-efficiency for long-running computation) influencing the growth of the serverless computing market.
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the serverless computing market.
• Market Development: In-depth understanding of upcoming technologies, research & development efforts, and new product & service releases in the serverless computing market.
• Market Diversification: Comprehensive details on the latest products & services, unexplored regions, recent advancements, and investments in the serverless computing market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies, and AWS (US), Microsoft (US), Google (US), IBM (US), Oracle (US), Alibaba Cloud (China), Tencent Cloud (China), DigitalOcean (US), Twilio (US), Cloudflare (US), MongoDB (US) among others in the serverless computing market.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
  • 1.2.1 INCLUSIONS AND EXCLUSIONS
• 1.3 MARKET SCOPE
  • 1.3.1 MARKET SEGMENTATION
  • 1.3.2 YEARS CONSIDERED
• 1.4 CURRENCY CONSIDERED
• 1.5 STAKEHOLDERS

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH APPROACH
  • 2.1.1 SECONDARY DATA
  • 2.1.2 PRIMARY DATA
    • 2.1.2.1 Breakup of primary profiles
    • 2.1.2.2 Key industry insights
• 2.2 MARKET BREAKUP AND DATA TRIANGULATION
• 2.3 MARKET SIZE ESTIMATION
• 2.4 MARKET FORECAST
• 2.5 RESEARCH ASSUMPTIONS
• 2.6 RESEARCH LIMITATIONS

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE GROWTH OPPORTUNITIES FOR PLAYERS IN SERVERLESS COMPUTING MARKET
• 4.2 SERVERLESS COMPUTING MARKET, BY SERVICE TYPE, 2024 VS. 2029
• 4.3 SERVERLESS COMPUTING MARKET, BY SERVICE MODEL, 2024 VS. 2029
• 4.4 SERVERLESS COMPUTING MARKET, BY DEPLOYMENT MODEL, 2024 VS. 2029
• 4.5 SERVERLESS COMPUTING MARKET, BY ORGANIZATION SIZE, 2024 VS. 2029
• 4.6 SERVERLESS COMPUTING MARKET, BY VERTICAL, 2024 VS. 2029
• 4.7 SERVERLESS COMPUTING MARKET, BY REGION, 2024 VS. 2029

5 MARKET OVERVIEW AND INDUSTRY TRENDS

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Increasing technological advancements
    • 5.2.1.2 Ongoing innovation in development tools and frameworks
    • 5.2.1.3 Better fault isolation and ease of integration using microservices architectures
    • 5.2.1.4 Shift from DevOps to serverless computing
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Loss of control over infrastructure
    • 5.2.2.2 Risk of vendor lock-in
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Microservice-based deployment
    • 5.2.3.2 Serverless backends in mobile and web development
    • 5.2.3.3 Increasing number of verticals utilizing distributed workloads
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Issues with third-party services
    • 5.2.4.2 Architectural and operational complexity
    • 5.2.4.3 Cost-efficiency for long-running computation
• 5.3 CASE STUDY ANALYSIS
  • 5.3.1 PLEXURE USES AZURE SERVERLESS TECHNOLOGIES TO SUPPORT HIGH PERFORMANCE & MINIMUM LATENCY REQUIREMENTS
  • 5.3.2 AWS LAMBDA HELPED FINANCIAL ENGINES REDUCE ITS ADMINISTRATIVE BURDEN
  • 5.3.3 IROBOT USED AWS' SERVICES TO CONTROL HEAVY TRAFFIC
  • 5.3.4 AWS HELPED NETFLIX IN ESTABLISHING SERVERLESS ARCHITECTURE
  • 5.3.5 SERVERLESS FRAMEWORK HELPED JOOT ACCELERATE DEVELOPMENT OF ITS SOCIAL MEDIA IMAGE OPTIMIZATION TOOL
• 5.4 ECOSYSTEM ANALYSIS
• 5.5 SUPPLY CHAIN ANALYSIS
• 5.6 PRICING ANALYSIS
  • 5.6.1 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY SOLUTION
  • 5.6.2 AVERAGE SELLING PRICE TREND, BY REGION
  • 5.6.3 AVERAGE SELLING PRICE TRENDS
• 5.7 PATENT ANALYSIS
• 5.8 TECHNOLOGY ANALYSIS
  • 5.8.1 KEY TECHNOLOGIES
    • 5.8.1.1 Event-driven programming
    • 5.8.1.2 Trigger-based tasks
    • 5.8.1.3 Microservices
    • 5.8.1.4 Runtime environments
    • 5.8.1.5 Stateless computing
  • 5.8.2 COMPLEMENTARY TECHNOLOGIES
    • 5.8.2.1 Asynchronous programming
    • 5.8.2.2 RESTful APIs
    • 5.8.2.3 DevOps
    • 5.8.2.4 Auto-scaling
    • 5.8.2.5 Infrastructure as Code (IaC)
  • 5.8.3 ADJACENT TECHNOLOGIES
    • 5.8.3.1 Containerization
    • 5.8.3.2 Kubernetes
    • 5.8.3.3 Edge computing
    • 5.8.3.4 Distributed tracing
    • 5.8.3.5 Self-healing
• 5.9 REGULATORY LANDSCAPE
  • 5.9.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 5.9.2 REGULATIONS, BY REGION
    • 5.9.2.1 North America
    • 5.9.2.2 Europe
    • 5.9.2.3 Asia Pacific
    • 5.9.2.4 Middle East & South Africa
    • 5.9.2.5 Latin America
  • 5.9.3 REGULATORY IMPLICATIONS AND INDUSTRY STANDARDS
    • 5.9.3.1 General Data Protection Regulation (GDPR)
    • 5.9.3.2 SEC Rule 17a-4
    • 5.9.3.3 ISO/IEC 27001
    • 5.9.3.4 System and Organization Controls 2 Type II Compliance
    • 5.9.3.5 Financial Industry Regulatory Authority (FINRA)
    • 5.9.3.6 Freedom of Information Act (FOIA)
    • 5.9.3.7 Health Insurance Portability and Accountability Act (HIPAA)
• 5.10 PORTER'S FIVE FORCES ANALYSIS
  • 5.10.1 THREAT OF NEW ENTRANTS
  • 5.10.2 THREAT OF SUBSTITUTES
  • 5.10.3 BARGAINING POWER OF SUPPLIERS
  • 5.10.4 BARGAINING POWER OF BUYERS
  • 5.10.5 INTENSITY OF COMPETITIVE RIVALRY
• 5.11 KEY CONFERENCES AND EVENTS IN 2024-2025
• 5.12 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS' BUSINESSES
• 5.13 KEY STAKEHOLDERS AND BUYING CRITERIA
  • 5.13.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.13.2 BUYING CRITERIA
• 5.14 BUSINESS MODEL ANALYSIS
• 5.15 INVESTMENT AND FUNDING SCENARIO
• 5.16 IMPACT OF AI/GEN AI ON SERVERLESS COMPUTING MARKET
  • 5.16.1 INDUSTRY TRENDS: USE CASES
    • 5.16.1.1 Healthcare & life sciences industry
    • 5.16.1.2 Retail industry
  • 5.16.2 TOP VENDORS ADAPTING TO GEN AI
    • 5.16.2.1 AWS
    • 5.16.2.2 Microsoft Azure

6 SERVERLESS COMPUTING MARKET, BY SERVICE TYPE

• 6.1 INTRODUCTION
  • 6.1.1 SERVICE TYPE: SERVERLESS COMPUTING MARKET DRIVERS
• 6.2 COMPUTE
  • 6.2.1 STREAMLINING CODE EXECUTION AND APPLICATION DEPLOYMENT WITH SERVERLESS FUNCTIONS AND CONTAINERS
  • 6.2.2 SERVERLESS FUNCTIONS
  • 6.2.3 SERVERLESS CONTAINERS
• 6.3 SERVERLESS STORAGE
  • 6.3.1 SCALABLE AND ON-DEMAND DATA STORAGE SOLUTIONS WITHOUT NEED FOR INFRASTRUCTURE MANAGEMENT
  • 6.3.2 OBJECT STORAGE
  • 6.3.3 BLOCK STORAGE
  • 6.3.4 FILE STORAGE
• 6.4 SERVERLESS DATABASE
  • 6.4.1 SERVERLESS DATABASE TO OFFER FULLY MANAGED, SCALABLE DATABASE SOLUTIONS THAT AUTOMATICALLY HANDLE INFRASTRUCTURE TASKS
  • 6.4.2 RELATIONAL DATABASES
  • 6.4.3 NON-RELATIONAL DATABASES
• 6.5 APPLICATION INTEGRATION
  • 6.5.1 SEAMLESS INTERACTION BETWEEN DISPARATE SYSTEMS AND APPLICATIONS USING APPLICATION INTEGRATION SERVICE
  • 6.5.2 EVENT-DRIVEN SERVICES
  • 6.5.3 MESSAGING SERVICES
  • 6.5.4 API MANAGEMENT
• 6.6 MONITORING & SECURITY
  • 6.6.1 SERVERLESS MONITORING TO PROVIDE REAL-TIME INSIGHTS INTO APPLICATION PERFORMANCE, RESOURCE UTILIZATION, AND OPERATIONAL METRICS
  • 6.6.2 SERVERLESS MONITORING
  • 6.6.3 SECURITY MANAGEMENT
• 6.7 OTHER SERVICE TYPES

7 SERVERLESS COMPUTING MARKET, BY SERVICE MODEL

• 7.1 INTRODUCTION
  • 7.1.1 SERVICE MODEL: SERVERLESS COMPUTING MARKET DRIVERS
• 7.2 FUNCTION-AS-A-SERVICE
  • 7.2.1 FAAS TO ENABLE DEPLOYMENT AND EXECUTION OF SPECIFIC FUNCTIONS IN REACTION TO EVENTS WITHOUT HANDLING SERVER INFRASTRUCTURE
  • 7.2.2 STREAM & BATCH PROCESSING
  • 7.2.3 REAL-TIME ANALYTICS
  • 7.2.4 MICROSERVICES ARCHITECTURE
  • 7.2.5 AUTOMATION & INTEGRATION
  • 7.2.6 OTHER FAAS MODELS
• 7.3 BACKEND-AS-A-SERVICE
  • 7.3.1 BACKEND-AS-A-SERVICE MODEL TO INCREASE FLEXIBILITY AND STREAMLINE BACKEND OPERATIONS IN SERVERLESS COMPUTING
  • 7.3.2 FILE STORAGE & MANAGEMENT
  • 7.3.3 USER AUTHENTICATION & MANAGEMENT
  • 7.3.4 DATABASE MANAGEMENT
  • 7.3.5 PUSH NOTIFICATIONS
  • 7.3.6 OTHER BAAS MODELS

8 SERVERLESS COMPUTING MARKET, BY DEPLOYMENT MODEL

• 8.1 INTRODUCTION
  • 8.1.1 DEPLOYMENT MODEL: SERVERLESS COMPUTING MARKET DRIVERS
• 8.2 PUBLIC CLOUD
  • 8.2.1 PUBLIC CLOUD DEPLOYMENT TO HELP IN QUICK DEPLOYMENT AND EXPANSION OF APPLICATIONS
• 8.3 PRIVATE CLOUD
  • 8.3.1 PRIVATE CLOUD TO CUSTOMIZE SERVERLESS ENVIRONMENTS WITH ENHANCED SECURITY AND INTEGRATION
• 8.4 HYBRID CLOUD
  • 8.4.1 HYBRID CLOUD MODEL TO OFFER BETTER DISASTER RECOVERY AND COMPLIANCE MANAGEMENT

9 SERVERLESS COMPUTING MARKET, BY ORGANIZATION SIZE

• 9.1 INTRODUCTION
  • 9.1.1 ORGANIZATION SIZE: SERVERLESS COMPUTING MARKET DRIVERS
• 9.2 SMALL ENTERPRISES
  • 9.2.1 SERVERLESS COMPUTING TO HELP REDUCE COSTS AND SCALE APPLICATIONS WITHOUT INFRASTRUCTURE HASSLES
• 9.3 MEDIUM ENTERPRISES
  • 9.3.1 SERVERLESS COMPUTING TO HANDLE FLUCTUATING WORKLOADS AND OPTIMIZE COSTS WITH RAPID DEPLOYMENT AND INTEGRATED SECURITY
• 9.4 LARGE ENTERPRISES
  • 9.4.1 SERVERLESS SOLUTIONS TO SCALE AND MANAGE HIGH-VOLUME OPERATIONS WITH MINIMAL INFRASTRUCTURE OVERHEAD

10 SERVERLESS COMPUTING MARKET, BY VERTICAL

• 10.1 INTRODUCTION
  • 10.1.1 VERTICAL: SERVERLESS COMPUTING MARKET DRIVERS
• 10.2 IT & TELECOM
  • 10.2.1 SERVERLESS COMPUTING TO OPTIMIZE OPERATIONS BY MINIMIZING INFRASTRUCTURE MANAGEMENT AND SCALING DYNAMICALLY
  • 10.2.2 IT & TELECOM: USE CASES
    • 10.2.2.1 Network function virtualization
    • 10.2.2.2 Real-time data processing
    • 10.2.2.3 Content delivery networks (CDNs)
• 10.3 BFSI
  • 10.3.1 SERVERLESS COMPUTING TO ENHANCE OPERATIONAL EFFICIENCY, AGILITY, AND INNOVATION
  • 10.3.2 BFSI: USE CASES
    • 10.3.2.1 Fraud detection
    • 10.3.2.2 Payment processing
    • 10.3.2.3 Customer data analytics
• 10.4 RETAIL & CONSUMER GOODS
  • 10.4.1 DYNAMIC SCALING OF ECOMMERCE PLATFORMS WITH SERVERLESS COMPUTING TO OPTIMIZE REAL-TIME TRAFFIC HANDLING DURING PEAK SALES
  • 10.4.2 RETAIL & CONSUMER GOODS: USE CASES
    • 10.4.2.1 Personalized marketing
    • 10.4.2.2 Inventory management
    • 10.4.2.3 eCommerce platforms
• 10.5 HEALTHCARE & LIFE SCIENCES
  • 10.5.1 SERVERLESS ARCHITECTURES TO FACILITATE SEAMLESS INTEGRATION AND SCALING OF SERVICES
  • 10.5.2 HEALTHCARE & LIFE SCIENCES: USE CASES
    • 10.5.2.1 Telemedicine
    • 10.5.2.2 Patient data management
    • 10.5.2.3 Genomic data processing
• 10.6 GOVERNMENT & DEFENSE
  • 10.6.1 SERVERLESS COMPUTING TO OPTIMIZE REAL-TIME COMMUNICATION AND RESOURCE MANAGEMENT IN DISASTER RESPONSE OPERATIONS
  • 10.6.2 GOVERNMENT & DEFENSE: USE CASES
    • 10.6.2.1 Smart city initiatives
    • 10.6.2.2 Citizen services portals
    • 10.6.2.3 Disaster response coordination
• 10.7 TRANSPORTATION & LOGISTICS
  • 10.7.1 SERVERLESS COMPUTING TO OFFER SCALABLE AND COST-EFFECTIVE SOLUTIONS TAILORED TO COMPLEX LOGISTICS NEEDS
  • 10.7.2 TRANSPORTATION & LOGISTICS
    • 10.7.2.1 Transportation & logistics: Use cases
      • 10.7.2.1.1 Fleet management
      • 10.7.2.1.2 Route optimization
      • 10.7.2.1.3 Shipment tracking
• 10.8 MANUFACTURING
  • 10.8.1 LEVERAGING SERVERLESS COMPUTING TO HELP IMPROVE PRODUCTIVITY, REDUCE DOWNTIME, AND MAINTAIN HIGH PRODUCT QUALITY STANDARDS
  • 10.8.2 MANUFACTURING: USE CASES
    • 10.8.2.1 Predictive analytics
    • 10.8.2.2 IoT integration
    • 10.8.2.3 Quality control
• 10.9 OTHER VERTICALS

11 SERVERLESS COMPUTING MARKET, BY REGION

• 11.1 INTRODUCTION
• 11.2 NORTH AMERICA
  • 11.2.1 NORTH AMERICA: SERVERLESS COMPUTING MARKET DRIVERS
  • 11.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
  • 11.2.3 US
    • 11.2.3.1 Robust digital infrastructure and supportive regulatory environment to boost market
  • 11.2.4 CANADA
    • 11.2.4.1 Cross-border trade and collaboration to accelerate adoption of serverless technologies
• 11.3 EUROPE
  • 11.3.1 EUROPE: SERVERLESS COMPUTING MARKET DRIVERS
  • 11.3.2 EUROPE: MACROECONOMIC OUTLOOK
  • 11.3.3 UK
    • 11.3.3.1 Advanced digital economy, strong technology sector, and proactive approach to cloud adoption to bolster market growth
  • 11.3.4 GERMANY
    • 11.3.4.1 Strategic interest in bolstering digital autonomy and competitiveness on global scale to drive market
  • 11.3.5 FRANCE
    • 11.3.5.1 Increasing adoption of innovative cloud solutions to propel market growth
  • 11.3.6 ITALY
    • 11.3.6.1 Country's trade relations and supply chain dynamics to aid market growth
  • 11.3.7 REST OF EUROPE
• 11.4 ASIA PACIFIC
  • 11.4.1 ASIA PACIFIC: SERVERLESS COMPUTING MARKET DRIVERS
  • 11.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
  • 11.4.3 CHINA
    • 11.4.3.1 Spike in demand for enhanced scalability and reduced operational costs to drive market
  • 11.4.4 INDIA
    • 11.4.4.1 Rapid digitization and government initiatives to fuel market growth
  • 11.4.5 JAPAN
    • 11.4.5.1 Robust cloud infrastructure, supported by skilled IT workforce to boost market growth
  • 11.4.6 REST OF ASIA PACIFIC
• 11.5 MIDDLE EAST & AFRICA
  • 11.5.1 MIDDLE EAST & AFRICA: SERVERLESS COMPUTING MARKET DRIVERS
  • 11.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
  • 11.5.3 GCC
    • 11.5.3.1 Saudi Arabia
      • 11.5.3.1.1 Substantial investments in smart cities, data centers, and AI-driven solutions to accelerate market growth
    • 11.5.3.2 UAE
      • 11.5.3.2.1 Government policies that promote digital transformation, AI adoption, and IoT integration to drive market
    • 11.5.3.3 Rest of GCC countries
  • 11.5.4 SOUTH AFRICA
    • 11.5.4.1 Growing digital economy and increasing cloud adoption to foster market growth
  • 11.5.5 REST OF MIDDLE EAST & AFRICA
• 11.6 LATIN AMERICA
  • 11.6.1 LATIN AMERICA: SERVERLESS COMPUTING MARKET DRIVERS
  • 11.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
  • 11.6.3 BRAZIL
    • 11.6.3.1 Significant global investment and strategic policy shifts to accelerate market growth
  • 11.6.4 MEXICO
    • 11.6.4.1 Spike in demand for digital transformation across various sectors to bolster market growth
  • 11.6.5 REST OF LATIN AMERICA

12 COMPETITIVE LANDSCAPE

• 12.1 INTRODUCTION
• 12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
• 12.3 MARKET SHARE ANALYSIS
• 12.4 SERVERLESS COMPUTING MARKET: VENDOR BRAND/ PRODUCT COMPARISON
  • 12.4.1 FUNCTION-AS-A-SERVICE
    • 12.4.1.1 AWS Lambda
    • 12.4.1.2 Azure Functions
    • 12.4.1.3 Google Cloud Functions
    • 12.4.1.4 IBM Cloud Functions
    • 12.4.1.5 Oracle Cloud Functions
  • 12.4.2 BACKEND-AS-A-SERVICE
    • 12.4.2.1 AWS DynamoDB
    • 12.4.2.2 Azure Cosmos DB
    • 12.4.2.3 Google Firestore
    • 12.4.2.4 MongoDB
    • 12.4.2.5 FaunaDB
• 12.5 REVENUE ANALYSIS
• 12.6 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
  • 12.6.1 STARS
  • 12.6.2 EMERGING LEADERS
  • 12.6.3 PERVASIVE PLAYERS
  • 12.6.4 PARTICIPANTS
  • 12.6.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
• 12.7 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
  • 12.7.1 PROGRESSIVE COMPANIES
  • 12.7.2 RESPONSIVE COMPANIES
  • 12.7.3 DYNAMIC COMPANIES
  • 12.7.4 STARTING BLOCKS
  • 12.7.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    • 12.7.5.1 Detailed list of key startups/SMEs
    • 12.7.5.2 Competitive benchmarking of startups/SMEs
• 12.8 COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS
• 12.9 COMPETITIVE SCENARIO AND TRENDS
  • 12.9.1 PRODUCT LAUNCHES & ENHANCEMENTS
  • 12.9.2 DEALS

13 COMPANY PROFILES

• 13.1 INTRODUCTION
• 13.2 MAJOR PLAYERS
  • 13.2.1 AWS
    • 13.2.1.1 Business overview
    • 13.2.1.2 Products/Solutions/Services offered
    • 13.2.1.3 Recent developments
      • 13.2.1.3.1 Product launches & enhancements
    • 13.2.1.4 MnM view
      • 13.2.1.4.1 Right to win
      • 13.2.1.4.2 Strategic choices
      • 13.2.1.4.3 Weaknesses and competitive threats
  • 13.2.2 MICROSOFT
    • 13.2.2.1 Business overview
    • 13.2.2.2 Products/Solutions/Services offered
    • 13.2.2.3 Recent developments
      • 13.2.2.3.1 Product launches & enhancements
    • 13.2.2.4 MnM view
      • 13.2.2.4.1 Right to win
      • 13.2.2.4.2 Strategic choices
      • 13.2.2.4.3 Weaknesses and competitive threats
  • 13.2.3 IBM
    • 13.2.3.1 Business overview
    • 13.2.3.2 Products/Solutions/Services offered
    • 13.2.3.3 Recent developments
      • 13.2.3.3.1 Product launches & enhancements
    • 13.2.3.4 MnM view
      • 13.2.3.4.1 Right to win
      • 13.2.3.4.2 Strategic choices
      • 13.2.3.4.3 Weaknesses and competitive threats
  • 13.2.4 GOOGLE
    • 13.2.4.1 Business overview
    • 13.2.4.2 Products/Solutions/Services offered
    • 13.2.4.3 Recent developments
      • 13.2.4.3.1 Product launches & enhancements
      • 13.2.4.3.2 Deals
    • 13.2.4.4 MnM view
      • 13.2.4.4.1 Right to win
      • 13.2.4.4.2 Strategic choices
      • 13.2.4.4.3 Weaknesses and competitive threats
  • 13.2.5 ORACLE
    • 13.2.5.1 Business overview
    • 13.2.5.2 Products/Solutions/Services offered
    • 13.2.5.3 Recent developments
      • 13.2.5.3.1 Product launches & enhancements
    • 13.2.5.4 MnM view
      • 13.2.5.4.1 Right to win
      • 13.2.5.4.2 Strategic choices
      • 13.2.5.4.3 Weaknesses and competitive threats
  • 13.2.6 ALIBABA CLOUD
    • 13.2.6.1 Business overview
    • 13.2.6.2 Products/Solutions/Services offered
    • 13.2.6.3 Recent developments
      • 13.2.6.3.1 Product launches & enhancements
  • 13.2.7 TENCENT CLOUD
    • 13.2.7.1 Business overview
    • 13.2.7.2 Products/Solutions/Services offered
  • 13.2.8 TWILIO
    • 13.2.8.1 Business overview
    • 13.2.8.2 Products/Solutions/Services offered
  • 13.2.9 CLOUDFLARE
    • 13.2.9.1 Business overview
    • 13.2.9.2 Products/Solutions/Services offered
    • 13.2.9.3 Recent developments
      • 13.2.9.3.1 Product launches & enhancements
      • 13.2.9.3.2 Deals
  • 13.2.10 MONGODB
    • 13.2.10.1 Business overview
    • 13.2.10.2 Products/Solutions/Services offered
    • 13.2.10.3 Recent developments
      • 13.2.10.3.1 Product launches & enhancements
      • 13.2.10.3.2 Deals
      • 13.2.10.3.3 Expansions
• 13.3 OTHER PLAYERS
  • 13.3.1 NETLIFY
  • 13.3.2 FASTLY
  • 13.3.3 AKAMAI
  • 13.3.4 DIGITALOCEAN
  • 13.3.5 DATADOG
  • 13.3.6 VERCEL
  • 13.3.7 SPOT BY NETAPP
  • 13.3.8 ELASTIC
  • 13.3.9 VMWARE
  • 13.3.10 BACKENDLESS
  • 13.3.11 FAUNADB
  • 13.3.12 SCALEWAY
  • 13.3.13 8BASE
  • 13.3.14 SUPABASE
  • 13.3.15 APPWRITE

14 ADJACENT AND RELATED MARKETS

• 14.1 INTRODUCTION
  • 14.1.1 RELATED MARKETS
• 14.2 CLOUD MOBILE BACKEND AS A SERVICE (BAAS) MARKET
• 14.3 SERVERLESS ARCHITECTURE MARKET

15 APPENDIX

• 15.1 DISCUSSION GUIDE
• 15.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 15.3 CUSTOMIZATION OPTIONS
• 15.4 RELATED REPORTS
• 15.5 AUTHOR DETAILS