Summary

The global streaming analytics market is predicted to reach from USD 29.53 billion in 2024 to USD 125.85 billion by 2029, with a CAGR of 33.6% during the forecast period. The utilization of streaming analytics has revolutionized how businesses operate by using real-time processing and data analytics. It allows businesses to observe and react to data instantly, providing quick insights for speedy decision-making. The streaming analytics market is growing quickly as businesses understand the importance of staying proactive on trends and addressing problems promptly. With the use of streaming analytics, organizations are improving operational efficiency, enhance customer experiences, and discover new growth opportunities.
“By offering, the software segment is projected to hold the largest market share during the forecast period.”
The software segment is expected to take the lead and dominate the largest share of the streaming analytics market. The increase is primarily driven by the increasing utilization of real-time data processing software. Businesses are relying increasingly on streaming analytics software to quickly analyze incoming data and make informed decisions, resulting in faster and better choices. The need for sophisticated analytics tools that offer instant insights and assist in enhancing operations is driving this shift. With an increasing number of organizations acknowledging the importance of real-time data, the software segment within the streaming analytics market is expected to experience significant growth.
“By processing type segment, real-time streaming is registered to grow at the highest CAGR during the forecast period.”
During the forecast period, real-time streaming is projected to have the highest compound annual growth rate (CAGR) in the streaming analytics market. This growth is due to the growing need for real-time data processing capabilities. Businesses utilize streaming analytics to quickly analyze data, leading to rapid decision-making based on real-time insights. With a greater understanding of the importance of real-time data analysis, the market for streaming analytics is expected to experience rapid growth. This increase demonstrates the overall trend of using up-to-date data to remain competitive and flexible in a rapidly changing digital environment.

“By data type, unstructured data is projected to hold largest market share during the forecast period”
Unstructured data type is anticipated to hold the largest market share in the streaming analytics market during the forecast period. This trend emphasizes the increasing significance of analyzing massive quantities of unstructured data, such as social media posts, videos, and sensor data, instantaneously. The demand for unstructured data type is rapidly increasing as businesses rely more on streaming analytics to derive insights from diverse and complex data sources. The ability to effectively examine and comprehend this data allows businesses to make quicker, more well-informed decisions. This means that unstructured data type is projected to be the primary focus in the field of streaming analytics, highlighting its crucial role in the market.

“By application, sales performance tracking is registered to have highest CAGR during the forecast period”
During the forecast period, sales performance tracking is expected to experience the highest CAGR in the streaming analytics market. The rise is mainly fueled by the growing need for real time data processing, helping companies in optimizing sales tactics and enhancing overall results. By utilizing streaming analytics businesses are able to get real-time sales data, which helps in quicker and better decision-making. Consequently, this application in the streaming analytics market is anticipated to grow at a faster rate underscoring its significance in improving sales procedures and accomplishing organizational goals.
“By vertical, the BFSI sector is projected to hold the largest market share during the forecast period.”
During the forecast period, the BFSI sector is anticipated to hold the largest market share in the streaming analytics market. This growth is being propelled by the growing demand to effectively gather and analyze vast amounts of data in real-time. Businesses within the BFSI industry are using streaming analytics solutions to extract important information from real-time data processing, leading to improved decision-making, fraud identification, risk mitigation, and customer satisfaction. As a result, the BFSI industry is expected to see notable expansion in the streaming analytics market.

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: 35%, Tier II: 45%, and Tier III: 20%
 By Designation: C-Level Executives: 35%, Directors: 25%, and Others: 40%
 By Region: North America – 40%, Europe – 20%, Asia Pacific – 30%, Middle East & Africa - 5%, and Latin America - 5%
Major vendors offering streaming analytics solution and services across the globe are IBM (US), Microsoft (US), Google (US), AWS (US), SAS Institute (US), SAP (Germany), Cloudera (US), Teradata (US), TIBCO (US), Software AG (Germany), Informatica (US), Intel (US), HPE (US), Adobe (US), Altair (US), Mphasis (India), Striim (US), Conviva (US), INETCO (Canada), WSO2 (US), Iguazio (Israel), Materialize (US), StarTree (US), Crosser (Sweden), Quix (UK), Lenses.io (UK), BangDB (India), Imply (US), Coralogix (Israel), Ververica (Germany), KX (US), Confluent (US), Estuary (US), Fivetran (US), Hazelcast (US), DataStax (US), Solace (Canada), Databricks (US), GridGain Systems (US).
Research Coverage
The market study covers streaming analytics across segments. It aims to estimate the market size and the growth potential across different segments, such as offering, model type, application, vertical, and region. It includes an in-depth competitive analysis of the key players in the market, their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.
Key Benefits of Buying the Report
The report would provide the market leaders/new entrants with information on the closest approximations of the revenue numbers for the overall market for streaming analytics and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the market's pulse and provides information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:

• Analysis of key drivers (rising demand for statistical computation and analysis of moving data streams, integration of edge computing to enhance real-time data processing, and increased need for hyper-personalized customer interactions), restraints (compatibility issues and higher expenses, and regulatory compliance complexity), opportunities (rising investments in industry 4.0, and ability to extract profound insights and precise decision-making), and challenges (managing volume and velocity of data streams, and issues related to data consistency)
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new solutions & service launches in the streaming analytics market.

• Market Development: Comprehensive information about lucrative markets – the report analyses the streaming analytics market across varied regions.

• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in streaming analytics market strategies; the report also helps stakeholders understand the pulse of the streaming analytics market and provides them with information on key market drivers, restraints, challenges, and opportunities.

• Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players such as Google (US), Microsoft (US), SAS Institute (US), and AWS (US) among others, in the streaming analytics market.

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Table of Contents

1 INTRODUCTION 35
1.1 STUDY OBJECTIVES 35
1.2 MARKET DEFINITION 35
1.2.1 INCLUSIONS AND EXCLUSIONS 36
1.3 MARKET SCOPE 37
1.3.1 MARKET SEGMENTATION 37
1.4 YEARS CONSIDERED 38
1.5 CURRENCY CONSIDERED 38
1.6 STAKEHOLDERS 39
1.7 SUMMARY OF CHANGES 39
2 RESEARCH METHODOLOGY 40
2.1 RESEARCH DATA 40
2.1.1 SECONDARY DATA 41
2.1.2 PRIMARY DATA 41
2.1.2.1 Breakup of primary profiles 42
2.1.2.2 Key insights from industry experts 42
2.2 DATA TRIANGULATION 43
2.3 MARKET SIZE ESTIMATION 44
2.3.1 TOP-DOWN APPROACH 44
2.3.2 BOTTOM-UP APPROACH 45
2.4 MARKET FORECAST 48
2.5 RESEARCH ASSUMPTIONS 49
2.6 RESEARCH LIMITATIONS 51
3 EXECUTIVE SUMMARY 52
4 PREMIUM INSIGHTS 59
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN STREAMING ANALYTICS MARKET 59
4.2 STREAMING ANALYTICS MARKET, BY KEY APPLICATIONS, 2024–2029 60
4.3 NORTH AMERICA: STREAMING ANALYTICS MARKET, BY OFFERING AND
KEY VERTICALS, 2024 60
4.4 STREAMING ANALYTICS MARKET, BY REGION, 2024 61
5 MARKET OVERVIEW AND INDUSTRY TRENDS 62
5.1 INTRODUCTION 62
5.2 MARKET DYNAMICS 62
 
5.2.1 DRIVERS 63
5.2.1.1 Rising demand for statistical computation and analysis of moving data streams 63
5.2.1.2 Integration of edge computing to enhance real-time data processing 63
5.2.1.3 Growing need for hyper-personalized customer interactions 63
5.2.2 RESTRAINTS 63
5.2.2.1 Compatibility issues and higher expenses 63
5.2.2.2 Regulatory compliance complexity 64
5.2.3 OPPORTUNITIES 64
5.2.3.1 Rising investments in Industry 4.0 64
5.2.3.2 Increasing integration of AI technologies for profound insights and precise decision-making 64
5.2.4 CHALLENGES 65
5.2.4.1 Managing growing volume and velocity of data streams 65
5.2.4.2 Issues related to data consistency 65
5.3 CASE STUDY ANALYSIS 65
5.3.1 CASE STUDY 1: TRANSFORMING ELEVATOR MAINTENANCE WITH AZURE BY LEVERAGING STREAMING ANALYTICS FOR PROACTIVE AND EFFICIENT OPERATIONS 65
5.3.2 CASE STUDY 2: UPS UTILIZES STRIIM AND GOOGLE BIGQUERY FOR AI-ENHANCED SECURE PACKAGE DELIVERY 66
5.3.3 CASE STUDY 3: REAL-TIME EXPERIMENT ANALYTICS WITH APACHE FLINK AT PINTEREST 66
5.3.4 CASE STUDY 4: ENHANCED OPERATIONAL EFFICIENCY AND STREAMLINED ALERT MANAGEMENT WITH CORALOGIX'S STREAMING ANALYTICS CAPABILITIES 67
5.3.5 CASE STUDY 5: NETFLIX ENHANCES STREAMING EXPERIENCE WITH REAL-TIME ANALYTICS USING APACHE DRUID 67
5.3.6 CASE STUDY 6: MACY’S APPROACHED STRIIM TO ENHANCE ITS OPERATIONAL EFFICIENCY 68
5.3.7 CASE STUDY 7: INETCO HELPED UBA IN ITS DIGITAL TRANSFORMATION STRATEGY BY EFFECTIVELY MANAGING TRANSACTION PERFORMANCE 69
5.3.8 CASE STUDY 8: STRIIM TRANSFORMS DISCOVERY HEALTH WITH REAL-TIME DATA FOR ENHANCED HEALTHCARE DELIVERY 69
5.4 EVOLUTION OF STREAMING ANALYTICS MARKET 70
5.5 ECOSYSTEM ANALYSIS 71
5.5.1 SOFTWARE PROVIDERS 73
5.5.2 SERVICE PROVIDERS 73
5.5.3 CLOUD PROVIDERS 74
5.5.4 END USERS 74
5.5.5 REGULATORY BODIES 74
5.6 TECHNOLOGY ANALYSIS 74
5.6.1 KEY TECHNOLOGIES 75
5.6.1.1 Data mining 75
5.6.1.2 Data warehousing 75
 
5.6.1.3 Data governance 75
5.6.1.4 Business intelligence 75
5.6.2 COMPLEMENTARY TECHNOLOGIES 76
5.6.2.1 Cloud computing 76
5.6.2.2 Internet of Things 76
5.6.2.3 Edge computing 76
5.6.3 ADJACENT TECHNOLOGIES 76
5.6.3.1 Machine learning 76
5.6.3.2 Data pipeline 77
5.6.3.3 Change data capture 77
5.6.3.4 NoSQL databases 77
5.7 SUPPLY CHAIN ANALYSIS 78
5.8 REGULATORY LANDSCAPE 79
5.8.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 79
5.8.2 REGULATIONS 82
5.8.2.1 North America 82
5.8.2.1.1 Personal Information Protection and Electronic Documents Act (PIPEDA) 82
5.8.2.1.2 California Consumer Privacy Act (CCPA) 83
5.8.2.1.3 Gramm-Leach-Bliley (GLB) Act 83
5.8.2.2 Europe 83
5.8.2.2.1 General Data Protection Regulation 83
5.8.2.2.2 Network and Information Systems Directive (NIS Directive) - European Union 83
5.8.2.2.3 Directive on Privacy and Electronic Communications (ePrivacy Directive) 84
5.8.2.3 Asia Pacific 84
5.8.2.3.1 Personal Data Protection Act 84
5.8.2.3.2 Act on the Protection of Personal Information 84
5.8.2.3.3 Critical Information Infrastructure 84
5.8.2.3.4 International Organization for Standardization 27001 85
5.8.2.4 Middle East & Africa 85
5.8.2.4.1 Protection of Personal Information Act (POPIA) - South Africa 85
5.8.2.4.2 Dubai Data Law - United Arab Emirates (UAE) 85
5.8.2.4.3 Nigerian Data Protection Regulation (NDPR) 85
5.8.2.5 Latin America 85
5.8.2.5.1 Brazil Data Protection Law 85
5.8.2.5.2 Argentina Personal Data Protection Law No. 25.326 86
5.8.2.5.3 Colombian Data Protection Laws 86
 
5.9 PATENT ANALYSIS 86
5.9.1 METHODOLOGY 86
5.9.2 PATENTS FILED, BY DOCUMENT TYPE 86
5.9.3 INNOVATIONS AND PATENT APPLICATIONS 87
5.10 KEY CONFERENCES AND EVENTS, 2024–2025 91
5.11 PORTER’S FIVE FORCES ANALYSIS 92
5.11.1 THREAT OF NEW ENTRANTS 93
5.11.2 THREAT OF SUBSTITUTES 93
5.11.3 BARGAINING POWER OF SUPPLIERS 93
5.11.4 BARGAINING POWER OF BUYERS 93
5.11.5 INTENSITY OF COMPETITIVE RIVALRY 93
5.12 PRICING ANALYSIS 94
5.12.1 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY TOP 3 APPLICATIONS 94
5.12.2 INDICATIVE PRICING ANALYSIS, BY OFFERING 95
5.13 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 96
5.14 KEY STAKEHOLDERS AND BUYING CRITERIA 97
5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS 97
5.14.2 BUYING CRITERIA 97
5.15 INVESTMENT AND FUNDING SCENARIO 98
5.16 IMPACT OF GENERATIVE AI ON STREAMING ANALYTICS MARKET 99
5.16.1 TOP USE CASES AND MARKET POTENTIAL 99
5.16.1.1 Key use cases 99
5.16.2 FRAUD DETECTION 100
5.16.3 PREDICTIVE ASSET MANAGEMENT 100
5.16.4 SUPPLY CHAIN MANAGEMENT 100
5.16.5 SALES PERFORMANCE TRACKING 100
5.16.6 LOCATION INTELLIGENCE 100
5.16.7 SOCIAL MEDIA MONITORING 100
6 STREAMING ANALYTICS MARKET, BY OFFERING 101
6.1 INTRODUCTION 102
6.1.1 OFFERING: STREAMING ANALYTICS MARKET DRIVERS 102
6.2 SOFTWARE 103
6.2.1 REVOLUTIONIZING REAL-TIME DECISION-MAKING WITH STREAMING ANALYTICS SOFTWARE 103
6.2.2 BY SOFTWARE TECHNOLOGY 104
6.2.2.1 Real-time data processing 105
6.2.2.2 Complex event processing 106
6.2.2.3 Data visualization & reporting 107
6.2.2.4 Event stream processing 108
6.2.2.5 Other software technologies 109
 
6.2.3 BY SOFTWARE DEPLOYMENT MODE 110
6.2.3.1 Cloud 111
6.2.3.1.1 Public 113
6.2.3.1.2 Private 114
6.2.3.1.3 Hybrid 115
6.2.3.2 On-premises 116
6.3 SERVICES 117
6.3.1 OPTIMIZING REAL-TIME DATA CAPABILITIES WITH STREAMING ANALYTICS SERVICES 117
6.3.2 PROFESSIONAL SERVICES 119
6.3.2.1 Consulting services 121
6.3.2.2 Deployment & integration services 122
6.3.2.3 Support & maintenance services 123
6.3.3 MANAGED SERVICES 124
7 STREAMING ANALYTICS MARKET, BY APPLICATION 126
7.1 INTRODUCTION 127
7.1.1 APPLICATION: STREAMING ANALYTICS MARKET DRIVERS 127
7.2 FRAUD DETECTION 130
7.2.1 UTILIZING REAL-TIME STREAMING ANALYTICS FOR EFFECTIVE FRAUD DETECTION 130
7.3 SALES PERFORMANCE TRACKING 131
7.3.1 LEVERAGING REAL-TIME STREAMING ANALYTICS FOR ENHANCED SALES PERFORMANCE MANAGEMENT 131
7.4 PREDICTIVE ASSET MANAGEMENT 132
7.4.1 ENHANCING ASSET RELIABILITY THROUGH STREAMING ANALYTICS PREDICTIVE INSIGHTS 132
7.5 RISK MANAGEMENT 133
7.5.1 RISK MANAGEMENT WITH STREAMING ANALYTICS ENHANCES DECISION-MAKING 133
7.6 NETWORK MANAGEMENT & OPTIMIZATION 134
7.6.1 ENHANCING NETWORK PERFORMANCE WITH REAL-TIME ANALYTICS 134
7.7 LOCATION INTELLIGENCE 135
7.7.1 LEVERAGING GEOSPATIAL DATA FOR STRATEGIC DECISION-MAKING 135
7.8 SUPPLY CHAIN MANAGEMENT 136
7.8.1 OPTIMIZING SUPPLY CHAINS WITH REAL-TIME MONITORING 136
7.9 CUSTOMER ACTIVITY MONITORING 137
7.9.1 BOOSTING CUSTOMER ENGAGEMENT AND INSIGHTS WITH STREAMING ANALYTICS 137
7.10 PRODUCT INNOVATION 138
7.10.1 UTILIZING DATA FOR FASTER PRODUCT DEVELOPMENT 138
7.11 SOCIAL MEDIA MONITORING 139
7.11.1 ENHANCING BRAND ENGAGEMENT WITH REAL-TIME SOCIAL INSIGHTS 139
 
7.12 REAL-TIME THREAT INTELLIGENCE 140
7.12.1 BOOSTING CYBERSECURITY WITH CONTINUOUS THREAT DETECTION USING STREAMING ANALYTICS 140
7.13 OTHER APPLICATIONS 141
8 STREAMING ANALYTICS MARKET, BY PROCESSING TYPE 142
8.1 INTRODUCTION 143
8.1.1 PROCESSING TYPE: STREAMING ANALYTICS MARKET DRIVERS 143
8.2 BATCH PROCESSING 144
8.2.1 BATCH PROCESSING ENHANCES SCALABILITY AND EFFICIENCY IN STREAMING ANALYTICS 144
8.3 REAL-TIME STREAMING 145
8.3.1 REAL-TIME STREAMING ANALYTICS ENABLES IMMEDIATE DATA INSIGHTS AND DECISION-MAKING ACROSS INDUSTRIES 145
9 STREAMING ANALYTICS MARKET, BY DATA TYPE 147
9.1 INTRODUCTION 148
9.1.1 DATA TYPE: STREAMING ANALYTICS MARKET DRIVERS 148
9.2 STRUCTURED 149
9.2.1 OPTIMIZING REAL-TIME PROCESSING WITH STRUCTURED DATA IN STREAMING ANALYTICS 149
9.3 UNSTRUCTURED 150
9.3.1 REAL-TIME ANALYSIS OF UNSTRUCTURED DATA DRIVES INNOVATION IN STREAMING ANALYTICS 150
10 STREAMING ANALYTICS MARKET, BY VERTICAL 152
10.1 INTRODUCTION 153
10.1.1 VERTICAL: STREAMING ANALYTICS MARKET DRIVERS 153
10.2 BFSI 155
10.2.1 LEVERAGING STREAMING ANALYTICS FOR REAL-TIME DECISION-MAKING AND FRAUD PREVENTION 155
10.2.2 MONEY LAUNDERING DETECTION 156
10.2.3 PAYMENT FRAUD DETECTION 156
10.2.4 STOCK MARKET SURVEILLANCE 157
10.2.5 REAL-TIME CREDIT SCORING 157
10.2.6 TRADE MONITORING 157
10.2.7 OTHER BFSI USE CASES 157
10.3 RETAIL & E-COMMERCE 158
10.3.1 OPTIMIZING REAL-TIME RETAIL STRATEGIES WITH STREAMING ANALYTICS 158
10.3.2 PERSONALIZED PRODUCT RECOMMENDATIONS 159
10.3.3 CUSTOMER SEGMENTATION 159
10.3.4 TREND PREDICTION 159
10.3.5 CUSTOMER 360 & OMNI-CHANNEL EXPERIENCE 160
 
10.3.6 RETAIL INVENTORY MANAGEMENT 160
10.3.7 OTHER RETAIL & E-COMMERCE USE CASES 160
10.4 HEALTHCARE & LIFE SCIENCES 160
10.4.1 REAL-TIME DATA REVOLUTIONIZING HEALTHCARE AND LIFE SCIENCES THROUGH STREAMING ANALYTICS 160
10.4.2 REAL-TIME ICU MONITORING 161
10.4.3 PREVENTIVE CARE 162
10.4.4 DIABETES MANAGEMENT 162
10.4.5 PATIENTS & CLINICAL INFORMATICS 162
10.4.6 CLINICAL DECISION SUPPORT SYSTEMS 162
10.4.7 OTHER HEALTHCARE & LIFE SCIENCES USE CASES 163
10.5 MEDIA & ENTERTAINMENT 163
10.5.1 STREAMING ANALYTICS DRIVE AUDIENCE ENGAGEMENT AND OPTIMIZE MONETIZATION IN MEDIA AND ENTERTAINMENT 163
10.5.2 PERSONALIZED CONTENT RECOMMENDATIONS 164
10.5.3 VIEWER INSIGHTS & OPTIMIZATION 165
10.5.4 ADVERTISING & TARGETED MARKETING STRATEGIES 165
10.5.5 CAMPAIGN OPTIMIZATION 165
10.5.6 CONTENT CREATION 166
10.5.7 OTHER MEDIA & ENTERTAINMENT USE CASES 166
10.6 TELECOMMUNICATIONS 166
10.6.1 ENHANCING TELECOM OPERATIONS AND CUSTOMER EXPERIENCE WITH REAL-TIME STREAMING ANALYTICS 166
10.6.2 REAL-TIME NETWORK MONITORING 167
10.6.3 AUTOMATED DIAGNOSTICS & OPTIMIZATION 168
10.6.4 AUTOMATED NETWORK ANALYSIS 168
10.6.5 NETWORK PLANNING 168
10.6.6 OTHER TELECOMMUNICATION USE CASES 168
10.7 GOVERNMENT & PUBLIC SECTOR 169
10.7.1 GROWING IMPORTANCE OF STREAMING ANALYTICS IN GOVERNMENT & PUBLIC SECTOR FOR REAL-TIME DECISION-MAKING 169
10.7.2 LAW ENFORCEMENT & PUBLIC SAFETY 170
10.7.3 REAL-TIME SURVEILLANCE & SECURITY 170
10.7.4 REAL-TIME INTELLIGENCE ANALYSIS 170
10.7.5 EMERGENCY RESPONSE OPTIMIZATION 171
10.7.6 OTHER GOVERNMENT & PUBLIC SECTOR USE CASES 171
10.8 MANUFACTURING 171
10.8.1 OPTIMIZING MANUFACTURING EFFICIENCY THROUGH REAL-TIME STREAMING ANALYTICS 171
10.8.2 PRODUCTION PLANNING & SCHEDULING 172
10.8.3 FAULT PREDICTION & PREDICTIVE MAINTENANCE 173
10.8.4 OPTIMIZING PRODUCT QUALITY 173
10.8.5 MONITORING PRODUCT LINES 173
10.8.6 DEMAND FORECASTING & INVENTORY MANAGEMENT 173
10.8.7 OTHER MANUFACTURING USE CASES 174
10.9 ENERGY & UTILITIES 174
10.9.1 OPTIMIZING ENERGY PRODUCTION AND DISTRIBUTION WITH REAL-TIME DATA INSIGHTS 174
10.9.2 REAL-TIME GRID MONITORING & MANAGEMENT 175
10.9.3 ENERGY OPTIMIZATION 175
10.9.4 ENERGY TRADING 175
10.9.5 GRID & ASSET PERFORMANCE OPTIMIZATION 176
10.9.6 OTHER ENERGY & UTILITIES USE CASES 176
10.10 TRANSPORTATION & LOGISTICS 176
10.10.1 OPTIMIZING OPERATIONS AND ENHANCING EFFICIENCY WITH REAL-TIME STREAMING ANALYTICS 176
10.10.2 REAL-TIME VEHICLE TRACKING 177
10.10.3 ROUTE OPTIMIZATION & FUEL EFFICIENCY 178
10.10.4 FLEET MANAGEMENT 178
10.10.5 DRIVER PERFORMANCE MONITORING 178
10.10.6 OTHER TRANSPORTATION & LOGISTICS USE CASES 178
10.11 OTHER VERTICALS 179
11 STREAMING ANALYTICS MARKET, BY REGION 180
11.1 INTRODUCTION 181
11.2 NORTH AMERICA 182
11.2.1 NORTH AMERICA: STREAMING ANALYTICS MARKET DRIVERS 183
11.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK 183
11.2.3 US 191
11.2.3.1 Rising need to shift toward more sophisticated and scalable streaming analytics solutions to boost market growth 191
11.2.4 CANADA 192
11.2.4.1 Rising need to enhance customer experience and optimize supply chain to drive market 192
11.3 EUROPE 193
11.3.1 EUROPE: STREAMING ANALYTICS MARKET DRIVERS 193
11.3.2 EUROPE: MACROECONOMIC OUTLOOK 193
11.3.3 UK 201
11.3.3.1 Growing need to extract insights from customer behavior and emerging trends to drive market 201
11.3.4 GERMANY 202
11.3.4.1 Rising need to handle growing volume of data to propel market 202
11.3.5 FRANCE 203
11.3.5.1 Rising demand for insight from continuous streams of data to boost market 203
 
11.3.6 ITALY 203
11.3.6.1 Rising demand for real-time insights and strategic cloud migrations to propel market 203
11.3.7 SPAIN 204
11.3.7.1 Rising need to enhance decision-making with real-time insight to boost market growth 204
11.3.8 REST OF EUROPE 205
11.4 ASIA PACIFIC 206
11.4.1 ASIA PACIFIC: STREAMING ANALYTICS MARKET DRIVERS 206
11.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK 206
11.4.3 CHINA 214
11.4.3.1 Rising investments by businesses in technologies to swiftly process data streams to boost market 214
11.4.4 JAPAN 215
11.4.4.1 Growing emphasis on technological innovation and robust IT infrastructure to propel market 215
11.4.5 INDIA 216
11.4.5.1 Increasing proliferation of IoT devices and rise of big data to boost market 216
11.4.6 SOUTH KOREA 217
11.4.6.1 Rising government investments and initiatives in smart city projects to propel market 217
11.4.7 ANZ 217
11.4.7.1 Rising demand for real-time data processing to drive market 217
11.4.8 SINGAPORE 218
11.4.8.1 Real-time data demand from various industries to drive market 218
11.4.9 REST OF ASIA PACIFIC 219
11.5 MIDDLE EAST & AFRICA 220
11.5.1 MIDDLE EAST & AFRICA: STREAMING ANALYTICS MARKET DRIVERS 220
11.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK 220
11.5.3 MIDDLE EAST 228
11.5.3.1 UAE 229
11.5.3.1.1 Commitment to technological innovation and digital transformation to fuel market growth 229
11.5.3.2 SAUDI ARABIA 230
11.5.3.2.1 Growing focus to gain actionable insights and enhance operational efficiency to drive market 230
11.5.3.3 QATAR 231
11.5.3.3.1 Growing demand for real-time data processing to provide valuable insights to drive market 231
11.5.3.4 TURKEY 231
11.5.3.4.1 Growing government support for digital infrastructure to propel market 231
11.5.3.5 REST OF MIDDLE EAST 232
11.5.4 AFRICA 233
11.6 LATIN AMERICA 234
11.6.1 LATIN AMERICA: STREAMING ANALYTICS MARKET DRIVERS 234
11.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK 234
11.6.3 BRAZIL 242
11.6.3.1 Rising need for real-time monitoring and data visualization to boost market 242
11.6.4 MEXICO 242
11.6.4.1 Need for real-time insights and operational efficiency to drive market 242
11.6.5 ARGENTINA 243
11.6.5.1 Growing adoption of cloud-based solutions and advancements in data processing technologies to boost market 243
11.6.6 REST OF LATIN AMERICA 244
12 COMPETITIVE LANDSCAPE 245
12.1 OVERVIEW 245
12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2023 245
12.3 REVENUE ANALYSIS 248
12.4 MARKET SHARE ANALYSIS 249
12.4.1 MARKET RANKING ANALYSIS 250
12.5 BRAND/PRODUCT COMPARISON 252
12.5.1 AMAZON KINESIS STREAMS (AWS) 252
12.5.2 GOOGLE CLOUD DATAFLOW (GOOGLE) 252
12.5.3 AZURE STREAM ANALYTICS (MICROSOFT) 253
12.5.4 RAPIDMINER (ALTAIR) 253
12.5.5 SPOTFIRE STREAMING ANALYTICS (TIBCO) 253
12.6 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 253
12.6.1 STARS 253
12.6.2 EMERGING LEADERS 253
12.6.3 PERVASIVE PLAYERS 254
12.6.4 PARTICIPANTS 254
12.6.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023 255
12.6.5.1 Company footprint 255
12.6.5.2 Region footprint 256
12.6.5.3 Offering footprint 257
12.6.5.4 Application footprint 258
12.6.5.5 Vertical footprint 259
12.7 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023 260
12.7.1 PROGRESSIVE COMPANIES 260
12.7.2 RESPONSIVE COMPANIES 260
12.7.3 DYNAMIC COMPANIES 260
12.7.4 STARTING BLOCKS 260
 
12.7.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023 262
12.7.5.1 Detailed list of key startups/SMEs 262
12.7.5.2 Competitive benchmarking of key startups/SMEs 264
12.8 COMPETITIVE SCENARIO AND TRENDS 265
12.8.1 PRODUCT LAUNCHES & ENHANCEMENTS 265
12.8.2 DEALS 267
12.9 COMPANY VALUATION AND FINANCIAL METRICS 269
12.9.1 STREAMING ANALYTICS MARKET: COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS 269
12.9.2 STREAMING ANALYTICS MARKET: YEAR-TO-DATE (YTD) PRICE TOTAL RETURN AND 5-YEAR STOCK BETA OF KEY VENDORS 270
13 COMPANY PROFILES 271
13.1 INTRODUCTION 271
13.2 KEY PLAYERS 271
13.2.1 IBM 271
13.2.1.1 Business overview 271
13.2.1.2 Products/Solutions/Services offered 272
13.2.1.3 Recent developments 273
13.2.1.4 MnM view 274
13.2.1.4.1 Key strengths 274
13.2.1.4.2 Strategic choices 274
13.2.1.4.3 Weaknesses and competitive threats 275
13.2.2 GOOGLE 276
13.2.2.1 Business overview 276
13.2.2.2 Products/Solutions/Services offered 277
13.2.2.3 Recent developments 278
13.2.2.4 MnM view 279
13.2.2.4.1 Key strengths 279
13.2.2.4.2 Strategic choices 279
13.2.2.4.3 Weaknesses and competitive threats 279
13.2.3 ORACLE 280
13.2.3.1 Business overview 280
13.2.3.2 Products/Solutions/Services offered 281
13.2.3.3 Recent developments 282
13.2.3.4 MnM view 283
13.2.3.4.1 Key strengths 283
13.2.3.4.2 Strategic choices 283
13.2.3.4.3 Weaknesses and competitive threats 283
13.2.4 MICROSOFT 284
13.2.4.1 Business overview 284
13.2.4.2 Products/Solutions/Services offered 285
13.2.4.3 Recent developments 286
13.2.4.4 MnM view 286
13.2.4.4.1 Key strengths 286
13.2.4.4.2 Strategic choices 287
13.2.4.4.3 Weaknesses and competitive threats 287
13.2.5 SAP 288
13.2.5.1 Business overview 288
13.2.5.2 Products/Solutions/Services offered 289
13.2.5.3 Recent developments 290
13.2.5.4 MnM view 290
13.2.5.4.1 Key strengths 290
13.2.5.4.2 Strategic choices 291
13.2.5.4.3 Weaknesses and competitive threats 291
13.2.6 SAS INSTITUTE 292
13.2.6.1 Business overview 292
13.2.6.2 Products/Solutions/Services offered 292
13.2.6.3 Recent developments 293
13.2.7 AWS 294
13.2.7.1 Business overview 294
13.2.7.2 Products/Solutions/Services offered 295
13.2.7.3 Recent developments 295
13.2.8 TIBCO 296
13.2.8.1 Business overview 296
13.2.8.2 Products/Solutions/Services offered 296
13.2.8.3 Recent developments 297
13.2.9 SOFTWARE AG 298
13.2.9.1 Business overview 298
13.2.9.2 Products/Solutions/Services offered 299
13.2.9.3 Recent developments 300
13.2.10 INFORMATICA 301
13.2.10.1 Business overview 301
13.2.10.2 Products/Solutions/Services offered 302
13.2.10.3 Recent developments 303
13.2.11 INTEL 304
13.2.12 CLOUDERA 305
13.2.13 HPE 306
13.2.14 TERADATA 307
13.2.15 ADOBE 308
13.2.16 ALTAIR 309
13.2.17 MPHASIS 310
13.2.18 KX 311
 
13.2.19 CONFLUENT 312
13.2.20 DATABRICKS 313
13.2.21 FIVETRAN 314
13.3 SMES/STARTUPS 315
13.3.1 DATASTAX 315
13.3.2 SOLACE 316
13.3.3 CONVIVA 317
13.3.4 STRIIM 318
13.3.5 INETCO 319
13.3.6 WSO2 320
13.3.7 IGUAZIO 321
13.3.8 MATERIALIZE 322
13.3.9 STARTREE 323
13.3.10 CROSSER 324
13.3.11 QUIX 325
13.3.12 LENSES.IO 326
13.3.13 BANGDB 327
13.3.14 IMPLY 328
13.3.15 CORALOGIX 329
13.3.16 VERVERICA 330
13.3.17 ESTUARY 331
13.3.18 HAZELCAST 332
13.3.19 GRIDGAIN SYSTEMS 333
14 ADJACENT AND RELATED MARKETS 334
14.1 INTRODUCTION 334
14.2 BIG DATA MARKET 334
14.2.1 MARKET DEFINITION 334
14.2.2 MARKET OVERVIEW 335
14.2.2.1 Big data market, by offering 336
14.2.2.2 Big data market, by business function 337
14.2.2.3 Big data market, by data type 338
14.2.2.4 Big data market, by vertical 339
14.2.2.5 Big data market, by region 340
14.3 VIDEO STREAMING SOFTWARE MARKET 341
14.3.1 MARKET DEFINITION 341
14.3.2 MARKET OVERVIEW 342
14.3.2.1 Video streaming software market, by offering 342
14.3.2.2 Video streaming software market, by streaming type 343
14.3.2.3 Video streaming software market, by deployment mode 344
14.3.2.4 Video streaming software market, by delivery channel 345
14.3.2.5 Video streaming software market, by monetization model 345
14.3.2.6 Video streaming software market, by connected device 346
14.3.2.7 Video streaming software market, by vertical 347
14.3.2.8 Video streaming software market, by region 348
15 APPENDIX 350
15.1 DISCUSSION GUIDE 350
15.2 CUSTOMIZATION OPTIONS 357
15.3 RELATED REPORTS 357
15.4 AUTHOR DETAILS 358