세계의 스트리밍 애널리틱스 시장(-2030년) : 제공별(이벤트 스트리밍 플랫폼, AI 스트리밍, IoT 스트리밍 플랫폼), 용도별(예지 보전, 공급망 최적화, 제품 혁신 및 관리, 리스크 및 위협 탐지) 예측(-2030년)

The streaming analytics market is experiencing strong growth, projected to rise from USD 4.34 billion in 2025 to USD 7.78 billion by 2030, at a CAGR of 12.4% during the forecast period. The growth of IoT devices, connected sensors, and telemetry is transforming the streaming analytics landscape by generating continuous, high-volume data streams that require real-time, in-motion analysis. Coupled with edge computing, data is processed near the source to reduce latency, optimize bandwidth, and maintain operations even with intermittent connectivity. This enables critical applications such as autonomous vehicles, industrial automation, and smart surveillance to make instant, data-driven decisions.

Edge processing also filters and summarizes data before transmission to the cloud, improving network efficiency and reducing server load. By combining IoT expansion with advanced edge analytics, organizations can extract actionable insights from vast streams of device and sensor data, enhancing operational responsiveness, predictive capabilities, and overall decision-making. These capabilities position streaming analytics as a vital tool for harnessing the increasing volume of real-time data in connected environments.

"AI/ML-driven streaming intelligence platforms will account for the fastest growth during the forecast period"

AI/ML-driven streaming intelligence platforms are leading the streaming analytics market by enabling organizations to derive real-time, predictive insights from continuous data flows. These platforms integrate artificial intelligence and machine learning with event streaming, enabling businesses to detect anomalies, forecast trends, and personalize customer experiences in real-time. Industries such as retail, BFSI, telecommunications, and manufacturing are leveraging these platforms for applications like fraud detection, network optimization, and supply chain efficiency. By combining automation, low-latency processing, and adaptive learning, AI/ML-driven streaming intelligence is setting the foundation for next-generation analytics and driving market leadership globally.

"Cloud deployment segment is expected to hold the largest market share during the forecast period"

Cloud deployment mode holds the largest market share in the streaming analytics market, driven by its scalability, cost efficiency, and rapid implementation capabilities. Enterprises are increasingly adopting cloud-based platforms to handle the massive data streams generated from IoT devices, digital applications, and omnichannel customer interactions. Cloud deployment enables real-time analytics with elastic compute resources, seamless integration with AI/ML models, and global accessibility. It also supports hybrid and multi-cloud strategies, giving organizations flexibility in managing diverse workloads. With enhanced security, continuous innovation, and reduced infrastructure overhead, cloud deployment has become the preferred choice for streaming analytics across industries worldwide.

"Real-time analytics platforms strengthen North America's market position, while Asia Pacific expands through high-volume data streaming"

North America remains the largest market for streaming analytics, supported by robust event-streaming infrastructure, widespread deployment of cloud-native data platforms, and the presence of leading technology vendors. Vendors are leveraging real-time analytics engines and integrated data pipelines to unify online and offline operations, optimize inventory flow, enhance customer engagement, and enable predictive decision-making. A focus on delivering hyper-personalized experiences, reducing operational latency, and deploying AI-powered insights across supply chains underscores the critical role of advanced streaming analytics platforms in maintaining competitive advantage.

In the Asia Pacific region, the market is expanding rapidly, driven by the adoption of high-throughput data processing platforms, the increasing number of real-time e-commerce transactions, and the integration of AI/ML for predictive customer insights. Key markets such as China, India, and South Korea are deploying streaming analytics to unify operations, enable personalized shopping journeys, and support large-scale decision-making. The growth of digital payments, IoT-enabled solutions, and government-led smart initiatives further accelerates adoption, establishing Asia Pacific as a key growth hub for streaming analytics worldwide.

Breakdown of Primaries

In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the streaming analytics market.

• By Company: Tier I - 25%, Tier II - 35%, and Tier III - 40%
• By Designation: C-Level Executives - 35%, D-Level Executives - 25%, and Others - 40%
• By Region: North America - 40%, Europe - 30%, Asia Pacific - 20%, Middle East & Africa - 5%, and Latin America - 5%

The report includes a study of key players offering streaming analytics solutions and services. The major market players include IBM (US), Google (US), Oracle (US), Microsoft (US), SAP (Germany), SAS Institute (US), AWS (US), TIBCO (US), Informatica (US), Cloudera (US), Snowflake (US), FICO (US), HPE (US), Teradata (US), Adobe (US), Altair (Siemens) (US), Mphasis (India), KX (FD Technologies) (US), Confluent (US), Databricks (US), Fivetran (US), Solace (Canada), Conviva (US), Striim (US), INETCO (Canada), WSO2 (US), Iguazio (McKinsey & Company) (Israel), Materialize (US), StarTree (US), Crosser (Sweden), Quix (England), Lenses.io (Celonis), BangDB (India), Imply.io (US), Coralogix (US), Ververica (Alibaba Group) (Germany), Estuary (US), Hazelcast (US), and GridGain Systems (US).

Research Coverage

The global streaming analytics market has been segmented based on the offering segment, which comprises software and services. The software segment is divided into the following categories: Event Streaming Platforms, Streaming Data Processing Engines, Data Ingestion & Integration Platforms, Complex Event Processing (CEP) Platforms, Real-Time Analytics & Visualization Platforms, AI/ML-Driven Streaming Intelligence Platforms, and IoT Streaming Platforms. The services segment is bifurcated into professional and managed services. Professional services include Training, Strategy and Consulting Services, System Integration & Implementation Services, and Support & Maintenance Services.

The deployment mode includes cloud, on-premises, and hybrid. The processing type is bifurcated into traditional streaming analytics (Basic event processing, Rule-based alerts, and Simple dashboards) and AI-powered streaming analytics (Machine learning analytics, Predictive analytics, Intelligent automation). The application segment includes Risk & Threat Detection, Customer Activity & Engagement Monitoring, Network & infrastructure Optimization, Predictive Maintenance, Supply Chain optimization, Operational Efficiency & Resource management, Sales Performance optimization, Product Innovation & Management, Media Quality & Experience Monitoring, Geospatial & Location Intelligence, and other applications (device & asset monitoring, compliance & audit monitoring). The vertical is bifurcated into BFSI, Retail & E-commerce, Healthcare & Life Sciences, Media & Entertainment, Telecommunications, Government & Defense, Manufacturing & Industrial IoT, Energy & Utilities, and Other verticals (Education, Travel & Hospitality), and region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America).

The report's scope encompasses detailed information on the drivers, restraints, challenges, and opportunities that influence the growth of the streaming analytics market. A detailed analysis of key industry players was conducted to provide insights into their business overview, solutions, and services, as well as key strategies, contracts, partnerships, agreements, product & service launches, mergers and acquisitions, and recent developments associated with the market. This report also covered the competitive analysis of upcoming startups in the market ecosystem.

Key Benefits of Buying the Report

The report will provide market leaders and new entrants with information on the closest approximations of the revenue numbers for the overall streaming analytics market and its subsegments. It will help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies. It will also help stakeholders understand the market's pulse and provide them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights into the following pointers:

• Analysis of key drivers (Continuous Data Streams Fuel Demand for Real-time analytics, Rising IoT Data Streams Accelerate Continuous Data Processing, Scalable and Integrated Platforms Enable Efficient Deployment), restraints (Limited Monitoring and Governance Increase Risks in Real-Time Data Processing), opportunities (Streaming Intelligence Accessibility Expanded by Low-Code and No-Code Tools, Quantum Technology Drives Next-Generation Data Insights), and challenges (Complexities in Maintaining Data Privacy and Regulatory Compliance)
• Product Development/Innovation: Detailed insights into upcoming technologies, research & development activities, and product & service launches in the streaming analytics
• Market Development: Comprehensive information about lucrative markets - analyzing the streaming analytics market across varied regions
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the streaming analytics market
• Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players such as IBM (US), Google (US), Oracle (US), Microsoft (US), SAP (Germany), SAS Institute (US), AWS (US), TIBCO (US), Informatica (US), Cloudera (US), Snowflake (US), FICO (US), HPE (US), Teradata (US), Adobe (US), Altair (Siemens) (US), Mphasis (India), KX (FD Technologies) (US), Confluent (US), Databricks (US), Fivetran (US), Solace (Canada), Conviva (US), Striim (US), INETCO (Canada), WSO2 (US), Iguazio (McKinsey & Company) (Israel), Materialize (US), StarTree (US), Crosser (Sweden), Quix (England), Lenses.io (Celonis), BangDB (India), Imply.io (US), Coralogix (US), Ververica (Alibaba Group) (Germany), Estuary (US), Hazelcast (US), and GridGain Systems (US).

The report also helps stakeholders understand the pulse of the streaming analytics market, providing them with information on key market drivers, restraints, challenges, and opportunities.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
• 1.3 STUDY SCOPE
  • 1.3.1 STREAMING ANALYTICS MARKET SEGMENTATION AND REGIONAL SCOPE
  • 1.3.2 INCLUSIONS AND EXCLUSIONS
  • 1.3.3 YEARS CONSIDERED
• 1.4 CURRENCY CONSIDERED
• 1.5 UNITS CONSIDERED
• 1.6 STAKEHOLDERS
• 1.7 SUMMARY OF CHANGES

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH DATA
  • 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
  • 2.3.1 TOP-DOWN APPROACH
  • 2.3.2 BOTTOM-UP APPROACH
• 2.4 MARKET FORECAST
• 2.5 RESEARCH ASSUMPTIONS
• 2.6 RESEARCH LIMITATIONS

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN STREAMING ANALYTICS MARKET
• 4.2 STREAMING ANALYTICS MARKET: TOP 3 SOFTWARE TYPES
• 4.3 NORTH AMERICA: STREAMING ANALYTICS MARKET, BY DEPLOYMENT MODE AND SOFTWARE TYPE
• 4.4 STREAMING ANALYTICS MARKET: BY REGION

5 MARKET OVERVIEW AND INDUSTRY TRENDS

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Expansion of statistical computation for moving data streams
    • 5.2.1.2 Rising IoT data streams accelerate continuous data processing
    • 5.2.1.3 Scalable and integrated platforms enable efficient deployment
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Limited monitoring and governance increase risks in real-time data processing
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Expansion of low-code/no-code platforms for broader adoption
    • 5.2.3.2 Quantum technology drives next-generation data insights
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Complexities in maintaining data privacy and regulatory compliance
• 5.3 IMPACT OF 2025 US TARIFFS-STREAMING ANALYTICS MARKET
  • 5.3.1 INTRODUCTION
  • 5.3.2 KEY TARIFF RATES
  • 5.3.3 PRICE IMPACT ANALYSIS
    • 5.3.3.1 Strategic shifts and emerging trends
  • 5.3.4 KEY IMPACTS ON VARIOUS REGIONS/COUNTRIES
    • 5.3.4.1 US
      • 5.3.4.1.1 Strategic shifts and key observations
    • 5.3.4.2 Asia Pacific
      • 5.3.4.2.1 Strategic shifts and key observations
    • 5.3.4.3 Europe
      • 5.3.4.3.1 Strategic shifts and key observations
  • 5.3.5 IMPACT ON END-USE INDUSTRIES
    • 5.3.5.1 Media & entertainment
    • 5.3.5.2 Retail & e-commerce
    • 5.3.5.3 Healthcare & life sciences
• 5.4 EVOLUTION OF STREAMING ANALYTICS MARKET
• 5.5 SUPPLY CHAIN ANALYSIS
• 5.6 ECOSYSTEM ANALYSIS
  • 5.6.1 STREAMING ANALYTICS PLATFORM PROVIDERS
  • 5.6.2 STREAMING DATA PROCESSING ENGINE PROVIDERS
  • 5.6.3 DATA INGESTION & INTEGRATION SOLUTION PROVIDERS
  • 5.6.4 REAL-TIME ANALYTICS & VISUALIZATION SOLUTION PROVIDERS
  • 5.6.5 AI/ML-DRIVEN STREAMING ANALYTICS PROVIDERS
• 5.7 INVESTMENT AND FUNDING SCENARIO
• 5.8 CASE STUDY ANALYSIS
  • 5.8.1 TRANSFORMING RELAYR CHALLENGES WITH AZURE FOR PROACTIVE AND EFFICIENT OPERATIONS
  • 5.8.2 REAL-TIME EXPERIMENT ANALYTICS WITH APACHE FLINK AT PINTEREST
  • 5.8.3 NETFLIX ENHANCES STREAMING EXPERIENCE WITH REAL-TIME ANALYTICS USING APACHE DRUID
  • 5.8.4 MACY'S APPROACHES STRIIM TO ENHANCE ITS OPERATIONAL EFFICIENCY
  • 5.8.5 STRIIM TRANSFORMS DISCOVERY HEALTH WITH REAL-TIME DATA FOR ENHANCED HEALTHCARE DELIVERY
• 5.9 TECHNOLOGY ANALYSIS
  • 5.9.1 KEY TECHNOLOGIES
    • 5.9.1.1 Real-time data serialization
    • 5.9.1.2 Machine learning
    • 5.9.1.3 Data governance
    • 5.9.1.4 Time-series processing
  • 5.9.2 COMPLEMENTARY TECHNOLOGIES
    • 5.9.2.1 Cloud Computing
    • 5.9.2.2 Internet of Things
    • 5.9.2.3 Edge Computing
  • 5.9.3 ADJACENT TECHNOLOGIES
    • 5.9.3.1 Data Pipeline and ETL
    • 5.9.3.2 NoSQL Databases
• 5.10 REGULATORY LANDSCAPE
  • 5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 5.10.2 KEY REGULATIONS
    • 5.10.2.1 North America
      • 5.10.2.1.1 US
      • 5.10.2.1.2 Canada
    • 5.10.2.2 Europe
      • 5.10.2.2.1 European Union
    • 5.10.2.3 Asia Pacific
      • 5.10.2.3.1 China
      • 5.10.2.3.2 India
      • 5.10.2.3.3 Japan
    • 5.10.2.4 Middle East & Africa
      • 5.10.2.4.1 UAE
      • 5.10.2.4.2 South Africa
    • 5.10.2.5 Latin America
      • 5.10.2.5.1 Brazil
      • 5.10.2.5.2 Argentina
• 5.11 PATENT ANALYSIS
  • 5.11.1 METHODOLOGY
  • 5.11.2 PATENTS FILED, BY DOCUMENT TYPE, 2016-2025
  • 5.11.3 INNOVATION AND PATENT APPLICATIONS
• 5.12 PRICING ANALYSIS
  • 5.12.1 AVERAGE SELLING PRICES OF OFFERINGS, BY KEY PLAYERS, 2025
  • 5.12.2 AVERAGE SELLING PRICES, BY APPLICATION, 2025
• 5.13 KEY CONFERENCES AND EVENTS, 2025-2026
• 5.14 PORTER'S FIVE FORCES ANALYSIS
  • 5.14.1 THREAT OF NEW ENTRANTS
  • 5.14.2 THREAT OF SUBSTITUTES
  • 5.14.3 BARGAINING POWER OF SUPPLIERS
  • 5.14.4 BARGAINING POWER OF BUYERS
  • 5.14.5 INTENSITY OF COMPETITIVE RIVALRY
• 5.15 KEY STAKEHOLDERS AND BUYING CRITERIA
  • 5.15.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.15.2 BUYING CRITERIA
• 5.16 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
• 5.17 IMPACT OF GENERATIVE AI ON STREAMING ANALYTICS MARKET
  • 5.17.1 TOP USE CASES AND MARKET POTENTIAL
    • 5.17.1.1 Key use cases
      • 5.17.1.1.1 Fraud detection
      • 5.17.1.1.2 Predictive asset management
      • 5.17.1.1.3 Supply chain management
      • 5.17.1.1.4 Sales performance tracking
      • 5.17.1.1.5 Location intelligence
      • 5.17.1.1.6 Social media monitoring

6 STREAMING ANALYTICS MARKET, BY OFFERING

• 6.1 INTRODUCTION
  • 6.1.1 OFFERING: STREAMING ANALYTICS MARKET DRIVERS
• 6.2 SOFTWARE
  • 6.2.1 EVENT STREAMING PLATFORMS
    • 6.2.1.1 Instant decision-making through high-performance data streaming to drive market
  • 6.2.2 STREAMING DATA PROCESSING ENGINES
    • 6.2.2.1 Unlocking real-time analytics to enhance business responsiveness
  • 6.2.3 DATA INGESTION & INTEGRATION PLATFORMS
    • 6.2.3.1 Scalable data workflows to empower analytics and intelligence
  • 6.2.4 COMPLEX EVENT PROCESSING PLATFORMS
    • 6.2.4.1 Enhanced operational agility through advanced event pattern recognition to accelerate market growth
  • 6.2.5 REAL-TIME ANALYTICS & VISUALIZATION PLATFORMS
    • 6.2.5.1 Optimized business performance through continuous data visualization insights to boost market
  • 6.2.6 AI/ML-DRIVEN STREAMING INTELLIGENCE PLATFORMS
    • 6.2.6.1 Detecting patterns and anomalies for faster, smarter decisions to drive market
  • 6.2.7 IOT STREAMING PLATFORMS
    • 6.2.7.1 Enhanced operational efficiency through real-time IoT data correlation to expand market reach
• 6.3 SERVICES
  • 6.3.1 IMPROVED OPERATIONAL PERFORMANCE WITH END-TO-END ANALYTICS SERVICE SUPPORT TO DRIVE MARKET
  • 6.3.2 PROFESSIONAL SERVICES
    • 6.3.2.1 Accelerated adoption and optimized performance for real-time analytics to drive market
    • 6.3.2.2 Training & consulting services
    • 6.3.2.3 System integration & implementation services
    • 6.3.2.4 Support & maintenance services
  • 6.3.3 MANAGED SERVICES
    • 6.3.3.1 Operational efficiency and maximizing value from data streams to drive market

7 STREAMING ANALYTICS MARKET, BY APPLICATION

• 7.1 INTRODUCTION
  • 7.1.1 APPLICATION: STREAMING ANALYTICS MARKET DRIVERS
• 7.2 RISK & THREAT DETECTION
  • 7.2.1 ENHANCEMENT OF ORGANIZATIONAL SECURITY THROUGH REAL-TIME THREAT IDENTIFICATION TO DRIVE MARKET
• 7.3 CUSTOMER ACTIVITY & ENGAGEMENT MONITORING
  • 7.3.1 UNLOCKING GROWTH OPPORTUNITIES THROUGH REAL-TIME ENGAGEMENT INTELLIGENCE TO ACCELERATE MARKET ADOPTION
• 7.4 NETWORK & INFRASTRUCTURE OPTIMIZATION
  • 7.4.1 PROACTIVELY MANAGING NETWORK RESOURCES USING PREDICTIVE ANALYTICS TOOLS TO BOOST MARKET EFFICIENCY
• 7.5 PREDICTIVE MAINTENANCE
  • 7.5.1 PRIORITIZING MAINTENANCE TASKS WITH RISK-BASED PREDICTIVE INSIGHTS TO EXPAND MARKET IMPACT
• 7.6 SUPPLY CHAIN OPTIMIZATION
  • 7.6.1 OPTIMIZATION OF INVENTORY AND LOGISTICS USING CONTINUOUS ANALYTICS MONITORING TO DRIVE MARKET
• 7.7 OPERATIONAL EFFICIENCY & RESOURCE MANAGEMENT
  • 7.7.1 REDUCING COSTS AND MAXIMIZING RESOURCES THROUGH DATA-DRIVEN ACTIONS TO PROPEL MARKET
• 7.8 SALES PERFORMANCE OPTIMIZATION
  • 7.8.1 SALES EFFICIENCY THROUGH CONTINUOUS PERFORMANCE MONITORING TOOLS TO ACCELERATE GROWTH
• 7.9 PRODUCT INNOVATION & MANAGEMENT
  • 7.9.1 REDUCING TIME-TO-MARKET THROUGH DATA-DRIVEN ACTIONS TO ENHANCE MARKET COMPETITIVENESS
• 7.10 MEDIA QUALITY & EXPERIENCE MONITORING
  • 7.10.1 IMPROVING DIGITAL CONTENT DELIVERY WITH REAL-TIME EXPERIENCE MONITORING TO OPTIMIZE MARKET REACH
• 7.11 GEOSPATIAL & LOCATION INTELLIGENCE
  • 7.11.1 RESOURCE OPTIMIZATION USING REAL-TIME INTELLIGENCE INSIGHTS TO BOOST MARKET EFFICIENCY
• 7.12 OTHER APPLICATIONS

8 STREAMING ANALYTICS MARKET, BY DEPLOYMENT MODE

• 8.1 INTRODUCTION
  • 8.1.1 DEPLOYMENT MODE: STREAMING ANALYTICS MARKET DRIVERS
• 8.2 CLOUD
  • 8.2.1 LEVERAGING CLOUD TO ACHIEVE SCALABLE, RELIABLE, AND EFFICIENT REAL-TIME ANALYTICS TO DRIVE MARKET
• 8.3 ON-PREMISES
  • 8.3.1 STRENGTHENED DATA MANAGEMENT AND COMPLIANCE FOR CONTINUOUS ANALYTICS TO DRIVE MARKET GROWTH
• 8.4 HYBRID
  • 8.4.1 REAL-TIME INSIGHTS WHILE ENSURING CONTROL AND OPERATIONAL EFFICIENCY TO ENHANCE MARKET IMPACT

9 STREAMING ANALYTICS MARKET, BY PROCESSING TYPE

• 9.1 INTRODUCTION
  • 9.1.1 PROCESSING TYPE: STREAMING ANALYTICS DRIVERS
• 9.2 TRADITIONAL STREAMING ANALYTICS
  • 9.2.1 ENHANCED ENTERPRISE AGILITY THROUGH REAL-TIME DATA MONITORING TO DRIVE MARKET
  • 9.2.2 BASIC EVENT PROCESSING
  • 9.2.3 RULE-BASED ALERTS
  • 9.2.4 SIMPLE DASHBOARDS
• 9.3 AI-POWERED STREAMING ANALYTICS
  • 9.3.1 OPTIMIZING BUSINESS PERFORMANCE THROUGH AI-ENHANCED DATA PROCESSING TO DRIVE MARKET
  • 9.3.2 MACHINE LEARNING ANALYTICS
  • 9.3.3 PREDICTIVE ANALYTICS
  • 9.3.4 INTELLIGENT AUTOMATION

10 STREAMING ANALYTICS MARKET, BY VERTICAL

• 10.1 INTRODUCTION
  • 10.1.1 VERTICALS: STREAMING ANALYTICS MARKET DRIVERS
• 10.2 BFSI
  • 10.2.1 SUPPORTING ALGORITHMIC TRADING WITH REAL-TIME MARKET AND OPERATIONAL DATA TO DRIVE MARKET
• 10.3 RETAIL & E-COMMERCE
  • 10.3.1 OPTIMIZING INVENTORY MANAGEMENT WITH CONTINUOUS STOCK AND DEMAND MONITORING TO BOOST MARKET IMPACT
• 10.4 HEALTHCARE & LIFE SCIENCES
  • 10.4.1 MONITORING CLINICAL TRIALS CONTINUOUSLY FOR FASTER RESEARCH AND COMPLIANCE TO DRIVE MARKET ADOPTION
• 10.5 MEDIA & ENTERTAINMENT
  • 10.5.1 ENHANCING VIEWER ENGAGEMENT THROUGH REAL-TIME CONTENT CONSUMPTION ANALYTICS TO BOOST MARKET TRACTION
• 10.6 TELECOMMUNICATIONS
  • 10.6.1 SUPPORTING 5G DEPLOYMENT WITH ACTIONABLE INSIGHTS FROM LIVE NETWORK STREAMS TO DRIVE MARKET
• 10.7 GOVERNMENT & DEFENSE
  • 10.7.1 DETECTING POTENTIAL THREATS USING PREDICTIVE STREAMING ANALYTICS CAPABILITIES TO PROPEL MARKET
• 10.8 MANUFACTURING & INDUSTRIAL IOT
  • 10.8.1 OPTIMIZING PRODUCTION WORKFLOWS USING CONTINUOUS REAL-TIME MACHINE MONITORING TO ACCELERATE GROWTH
• 10.9 ENERGY & UTILITIES
  • 10.9.1 STRENGTHENING GRID RELIABILITY BY LEVERAGING DATA-DRIVEN ANALYTICS SOLUTIONS TO DRIVE MARKET
• 10.10 TRANSPORTATION & LOGISTICS
  • 10.10.1 ENHANCING DELIVERY ACCURACY AND RESPONSIVENESS WITH STREAMING DATA TO DRIVE MARKET ADOPTION
• 10.11 OTHER VERTICALS

11 STREAMING ANALYTICS MARKET, BY REGION

• 11.1 INTRODUCTION
• 11.2 NORTH AMERICA
  • 11.2.1 NORTH AMERICA: STREAMING ANALYTICS MARKET DRIVERS
  • 11.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
  • 11.2.3 US
    • 11.2.3.1 Leveraging AI and predictive analytics for informed decision-making to drive market
  • 11.2.4 CANADA
    • 11.2.4.1 Strengthening energy infrastructure with predictive and real-time capabilities to drive market
• 11.3 EUROPE
  • 11.3.1 EUROPE: STREAMING ANALYTICS MARKET DRIVERS
  • 11.3.2 EUROPE: MACROECONOMIC OUTLOOK
  • 11.3.3 UK
    • 11.3.3.1 Maximizing compliance and efficiency using real-time data solutions to drive market
  • 11.3.4 GERMANY
    • 11.3.4.1 Optimizing logistics and supply chain using continuous data streams to drive market
  • 11.3.5 FRANCE
    • 11.3.5.1 Leveraging cloud-native and hybrid architectures for scalable analytics deployment to drive market
  • 11.3.6 REST OF EUROPE
• 11.4 ASIA PACIFIC
  • 11.4.1 ASIA PACIFIC: STREAMING ANALYTICS MARKET DRIVERS
  • 11.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
  • 11.4.3 CHINA
    • 11.4.3.1 Enhancing user engagement and competitive positioning through analytics to drive market
  • 11.4.4 INDIA
    • 11.4.4.1 Strategic partnerships driving innovation and enhanced analytics capabilities to propel market
  • 11.4.5 JAPAN
    • 11.4.5.1 Optimizing customer experiences and risk management via predictive insights to drive market
  • 11.4.6 SOUTH KOREA
    • 11.4.6.1 Leveraging cloud-native platforms for scalable, low-latency processing to drive market
  • 11.4.7 REST OF ASIA PACIFIC
• 11.5 MIDDLE EAST & AFRICA
  • 11.5.1 MIDDLE EAST & AFRICA: STREAMING ANALYTICS MARKET DRIVERS
  • 11.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
  • 11.5.3 SAUDI ARABIA
    • 11.5.3.1 Advancing Saudi streaming analytics through Vision 2030 and rigorous data protection frameworks to drive market
  • 11.5.4 UAE
    • 11.5.4.1 Enhancing security and operations through real-time video analytics to drive market
  • 11.5.5 SOUTH AFRICA
    • 11.5.5.1 Transforming content delivery through streaming partnerships to boost demand
  • 11.5.6 REST OF MIDDLE EAST & AFRICA
• 11.6 LATIN AMERICA
  • 11.6.1 LATIN AMERICA: STREAMING ANALYTICS MARKET DRIVERS
  • 11.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
  • 11.6.3 BRAZIL
    • 11.6.3.1 Leveraging real-time data for enhanced viewer engagement and operational efficiency to drive market
  • 11.6.4 MEXICO
    • 11.6.4.1 Optimizing content delivery through streaming analytics and cloud collaborations to drive market
  • 11.6.5 REST OF LATIN AMERICA

12 COMPETITIVE LANDSCAPE

• 12.1 OVERVIEW
• 12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2022-2025
• 12.3 REVENUE ANALYSIS, 2020-2024
• 12.4 MARKET SHARE ANALYSIS, 2024
• 12.5 PRODUCT COMPARISON
  • 12.5.1 PRODUCT COMPARATIVE ANALYSIS, BY PROCESSING TYPE (TRADITIONAL STREAMING ANALYTICS)
    • 12.5.1.1 IBM Event Streams (IBM)
    • 12.5.1.2 Azure Stream Analytics (Microsoft)
    • 12.5.1.3 Oracle Stream Analytics (Oracle)
    • 12.5.1.4 TIBCO Streaming (TIBCO)
    • 12.5.1.5 SAS Event Stream Processing (SAS Institute)
  • 12.5.2 PRODUCT COMPARATIVE ANALYSIS, BY PROCESSING TYPE (AI-POWERED STREAMING ANALYTICS)
    • 12.5.2.1 Databricks Data Intelligence Platform (Databricks)
    • 12.5.2.2 Confluent Platform (Confluent)
    • 12.5.2.3 Iguazio AI Platform (Iguazio)
    • 12.5.2.4 Striim Platform (Striim)
    • 12.5.2.5 Materialize software (Materialize)
• 12.6 COMPANY VALUATION AND FINANCIAL METRICS
• 12.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
  • 12.7.1 STARS
  • 12.7.2 EMERGING LEADERS
  • 12.7.3 PERVASIVE PLAYERS
  • 12.7.4 PARTICIPANTS
  • 12.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
    • 12.7.5.1 Company footprint
    • 12.7.5.2 Regional footprint
    • 12.7.5.3 Offering footprint
    • 12.7.5.4 Application footprint
    • 12.7.5.5 Vertical footprint
• 12.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
  • 12.8.1 PROGRESSIVE COMPANIES
  • 12.8.2 RESPONSIVE COMPANIES
  • 12.8.3 DYNAMIC COMPANIES
  • 12.8.4 STARTING BLOCKS
  • 12.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
    • 12.8.5.1 Detailed list of key startups/SMEs
    • 12.8.5.2 Competitive benchmarking of key startups/SMEs
• 12.9 COMPETITIVE SCENARIO
  • 12.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS
  • 12.9.2 DEALS

13 COMPANY PROFILES

• 13.1 INTRODUCTION
• 13.2 KEY PLAYERS
  • 13.2.1 IBM
    • 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 enhancements
      • 13.2.1.3.2 Deals
    • 13.2.1.4 MnM view
      • 13.2.1.4.1 Key strengths
      • 13.2.1.4.2 Strategic choices
      • 13.2.1.4.3 Weaknesses and competitive threats
  • 13.2.2 GOOGLE
    • 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 enhancements
      • 13.2.2.3.2 Deals
    • 13.2.2.4 MnM view
      • 13.2.2.4.1 Key strengths
      • 13.2.2.4.2 Strategic choices
      • 13.2.2.4.3 Weaknesses and competitive threats
  • 13.2.3 ORACLE
    • 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 Enhancements
      • 13.2.3.3.2 Deals
    • 13.2.3.4 MnM view
      • 13.2.3.4.1 Key strengths
      • 13.2.3.4.2 Strategic choices
      • 13.2.3.4.3 Weaknesses and competitive threats
  • 13.2.4 MICROSOFT
    • 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 enhancements
      • 13.2.4.3.2 Deals
    • 13.2.4.4 MnM view
      • 13.2.4.4.1 Key strengths
      • 13.2.4.4.2 Strategic choices
      • 13.2.4.4.3 Weaknesses and competitive threats
  • 13.2.5 SAP
    • 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 enhancements
      • 13.2.5.3.2 Deals
    • 13.2.5.4 MnM view
      • 13.2.5.4.1 Key strengths
      • 13.2.5.4.2 Strategic choices
      • 13.2.5.4.3 Weaknesses and competitive threats
  • 13.2.6 SAS INSTITUTE
    • 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 enhancements
      • 13.2.6.3.2 Deals
  • 13.2.7 AWS
    • 13.2.7.1 Business overview
    • 13.2.7.2 Products/Solutions/Services offered
    • 13.2.7.3 Recent developments
      • 13.2.7.3.1 Product enhancements
      • 13.2.7.3.2 Deals
  • 13.2.8 TIBCO
    • 13.2.8.1 Business overview
    • 13.2.8.2 Products/Solutions/Services offered
    • 13.2.8.3 Recent developments
      • 13.2.8.3.1 Product enhancements
      • 13.2.8.3.2 Deals
  • 13.2.9 INFORMATICA
    • 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 enhancements
      • 13.2.9.3.2 Deals
  • 13.2.10 CLOUDERA
    • 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 enhancements
      • 13.2.10.3.2 Deals
  • 13.2.11 SNOWFLAKE
  • 13.2.12 FICO
  • 13.2.13 HPE
  • 13.2.14 TERADATA
  • 13.2.15 ADOBE
  • 13.2.16 ALTAIR (SIEMENS)
  • 13.2.17 MPHASIS
  • 13.2.18 KX
  • 13.2.19 CONFLUENT
  • 13.2.20 DATABRICKS
  • 13.2.21 FIVETRAN
• 13.3 OTHER PLAYERS
  • 13.3.1 SOLACE
  • 13.3.2 CONVIVA
  • 13.3.3 STRIIM
  • 13.3.4 INETCO
  • 13.3.5 WSO2
  • 13.3.6 IGUAZIO (MCKINSEY & COMPANY)
  • 13.3.7 MATERIALIZE
  • 13.3.8 STARTREE
  • 13.3.9 CROSSER
  • 13.3.10 QUIX
  • 13.3.11 LENSES.IO
  • 13.3.12 BANGDB
  • 13.3.13 IMPLY.IO
  • 13.3.14 CORALOGIX
  • 13.3.15 VERVERICA
  • 13.3.16 ESTUARY
  • 13.3.17 HAZELCAST
  • 13.3.18 GRIDGAIN SYSTEMS

14 ADJACENT AND RELATED MARKETS

• 14.1 INTRODUCTION
• 14.2 BIG DATA MARKET-GLOBAL FORECAST TO 2028
  • 14.2.1 MARKET DEFINITION
  • 14.2.2 MARKET OVERVIEW
    • 14.2.2.1 Big data market, by offering
    • 14.2.2.2 Big data market, by business function
    • 14.2.2.3 Big data market, by data type
    • 14.2.2.4 Big data market, by vertical
    • 14.2.2.5 Big data market, by region
• 14.3 VIDEO STREAMING SOFTWARE MARKET
  • 14.3.1 MARKET DEFINITION
  • 14.3.2 MARKET OVERVIEW
    • 14.3.2.1 Video streaming software market, by offering
    • 14.3.2.2 Video streaming software market, by streaming type
    • 14.3.2.3 Video streaming software market, by deployment mode
    • 14.3.2.4 Video streaming software market, by vertical
    • 14.3.2.5 Video streaming software market, by region

15 APPENDIX

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