Streaming Analytics Market by Technology (Real-time Data Processing, Complex Event Processing, Data Visualization & Reporting, Event Stream Processing), Application (Fraud Detection, Predictive Asset Management, Risk Management) - Global Forecast to 2029
[358 Pages Report] The streaming analytics market is anticipated to grow from USD 29.53 billion in 2024 to USD 125.85 billion in 2029, at a CAGR of 33.6% during the forecast period. One of the market’s key growth drivers is the rising demand for handling data in real-time. Streaming analytics allows companies to improve operational efficiency by constantly gathering, processing, and examining data from various sources. It also allows businesses across various sectors to enhance decision-making and quickly identify irregularities, leading to improved customer experience and lower operational expenses. BFSI companies, for instance, utilize streaming analytics to analyze data instantly, leading to a notable enhancement in financial inclusivity. This may lead to rapid loan disbursement, fraud identification, and early anticipation of loan defaults, resulting in enhanced operational efficiency and increased profits. Retail and e-commerce companies can also utilize streaming analytics to improve efficiency, cut costs through cloud migration, enhance customer interactions, accelerate application rollouts, and bolster overall digital transformation initiatives to remain competitive in the market.
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Market Dynamics
Driver: Integration of edge computing in streaming analytics to enhance real-time data processing
The integration of edge computing is significant for the growth of the streaming analytics market, facilitating real-time data processing for quick decision-making. Businesses can quickly analyze data streams and gain valuable insights with low latency by processing data at the edge instead of centrally. This feature allows businesses to promptly react to important occurrences, improving operational effectiveness and customer interaction. The streaming analytics market is set to experience substantial growth due to the increasing use of IoT devices and the growing need for instant data analysis in sectors such as healthcare, manufacturing, and telecommunications. Furthermore, integrating edge computing with streaming analytics decreases the volume of data sent to central servers, alleviating bandwidth constraints and improving security by storing confidential data on local devices.
Restraint: Integration and compatibility issues with legacy systems
The growth of the streaming analytics market is significantly hindered by the integration and compatibility issues with legacy systems and higher expenses. Businesses across various sectors, such as manufacturing and energy & utilities, depend on legacy systems that do not have the flexibility and computational capacity needed for contemporary streaming analytics. These legacy systems frequently use unique formats and inflexible structures, causing challenges when trying to connect to modern streaming analytics solutions. This leads to complex, costly, and time-consuming integration processes that may hinder the adoption of modern technologies. Moreover, legacy systems might not have the ability to process data in real-time, which can decrease the effectiveness of streaming analytics and hinder the ability to quickly gain useful insights.
Opportunity: Increasing integration of AI and ML technologies to enhance real-time decision-making and operational efficiency
The growing demand for the integration of AI and ML technologies in streaming analytics provides a great opportunity for companies to improve real-time data processing. AI and ML algorithms enable businesses to quickly discover patterns and trends in large volumes of data using automated analytics. This feature is particularly beneficial in industries such as BFSI and healthcare & life sciences, where timely information can greatly affect results. AI-driven streaming analytics assists businesses in anticipating customer behavior and market trends, resulting in enhanced strategic planning and risk management. The shift toward automation aligns with the growing need for decision-making based on data analysis. By utilizing these technologies, businesses can improve operational efficiency and provide customized customer interactions, boosting their competitive advantage in the rapidly changing digital environment.
Challenge: Managing growing volume and velocity of data streams
The growth of the streaming analytics market is restricted by the growing volume and velocity of data streams. As businesses across different industries increasingly rely on real-time data for decision-making, they must tackle the challenge of handling and analyzing large amounts of continuously produced data. Traditional analytics systems may have difficulty processing vast quantities of data, necessitating the adoption of sophisticated, scalable systems capable of handling high-volume data streams. Furthermore, complexity also rises as the rate at which data is generated and needs to be managed, which is called data velocity, accelerates. The need for rapid data processing to provide useful insights is high, pushing current technologies to their limits and necessitating advancements in real-time analytics. The need for large-scale infrastructure and advanced analytical tools poses a challenge for organizations, hindering growth and increasing costs in the streaming analytics market
Impact of Generative AI in Streaming Analytics Market
Streaming Analytics Market Ecosystem
The streaming analytics market ecosystem comprises software providers, service providers, cloud providers, regulatory bodies, and end users. Together, they facilitate immediate data processing through the provision of tools, infrastructure, compliance, and implementation, aiding sectors in extracting insights, enhancing productivity, and influencing well-informed decision-making, all the while safeguarding data security and privacy.
By vertical, BFSI segment to account for largest market share during forecast period.
During the forecast period, the BFSI segment is estimated to hold the largest market share. The BFSI sector is rapidly implementing streaming analytics solutions to greatly improve operational efficiency and data-informed decision-making. Utilizing streaming analytics allows financial institutions to analyze data in real time, keeping a constant watch on transactions for fraud detection and anomaly recognition. It further improves risk management and ensures compliance with regulations, allowing businesses to respond promptly to potential threats. Additionally, personalized customer experiences are made possible by streaming analytics that examine user actions immediately to deliver highly tailored services and promotions.
By application, fraud detection segment to hold largest market share during forecast period.
During the forecast period, the fraud detection segment is anticipated to hold the largest market share. This growth is driven by the increasing complexity of cyber threats and the rising prevalence of online fraud across sectors such as BFSI, healthcare, and e-commerce. With the growing dependence of businesses on digital transactions, there has been a significant increase in the need for streaming analytics to identify fraudulent activities. These solutions use real-time data analysis and machine learning algorithms to detect suspicious patterns and reduce risks before they worsen. Through the examination of transaction patterns and other data streams in real time, streaming analytics enable companies to preemptively tackle risks, improve security, and avoid considerable monetary losses.
North America to account for largest market share during forecast period.
North America is estimated to hold the largest share of the streaming analytics market during the forecast period. This growth is primarily driven by the extensive use of IoT devices and the growing integration of AI and ML technologies. These advancements are enhancing the capability to process real-time data and offering valuable insights for different industries. Furthermore, the presence of several vendors offering streaming analytics solutions has also boosted the growth of the streaming analytics market across North America.
Key Market Players
The major software and service providers in the streaming analytics market include 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), and GridGain Systems (US). These companies have used organic and inorganic growth strategies, such as product launches, acquisitions, and partnerships, to strengthen their position in the market.
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Scope of the Report
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Report Metrics |
Details |
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Market size available for years |
2019–2029 |
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Base year considered |
2023 |
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Forecast period |
2024–2029 |
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Forecast units |
USD Billion |
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Segments covered |
Offering, Application, Processing Type, Data Type, Vertical, and Region |
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Geographies covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
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Companies covered |
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), and GridGain Systems (US) |
This research report categorizes the streaming analytics market based on offering, application, vertical, and region.
Offering:
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Software
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By technology
- Real-Time Data Processing
- Complex Event Processing
- Data Visualization & Reporting
- Event Stream Processing
- Others (Data Ingestion, and Data Storage)
- By Deployment Mode
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Cloud
- Public
- Private
- Hybrid
- On-Premises
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By technology
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Services
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Professional Services
- Consulting services
- Deployment & integration services
- Support and Maintenance services
- Managed Services
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Professional Services
By Application:
- Fraud Detection
- Sales Performance Tracking
- Predictive Asset Management
- Risk Management
- Network Management & Optimization
- Location Intelligence
- Supply Chain Management
- Customer Activity Monitoring
- Product Innovation
- Social Media Monitoring
- Real-Time Threat Intelligence
- Other Applications
By processing type:
- Batch Processing
- Real-Time Streaming
By data type:
- Structured
- Unstructured
By Verticals:
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BFSI
- Money Laundering Detection
- Payment Fraud Detection
- Stock Market Surveillance
- Real-Time Credit Scoring
- Trade Monitoring
- Others (Market Risk Analysis, Operational & Liquidity Risk)
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Retail & Ecommerce
- Personalized Product Recommendations
- Customer Segmentation
- Trend Prediction
- Customer 360 & Omni Channel Experience
- Retail Inventory Management
- Others (Point of Sale Management, Dynamic Product Bundling)
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Healthcare & Life Sciences
- Real-Time ICU Monitoring
- Preventive Care
- Diabetes Management
- Patients & Clinical Informatics
- Clinical Decision Support System
- Others (Telehealth Services, Clinical Data Management)
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Media & Entertainment
- Personalized Content Recommendations
- Viewer Insights & Optimization
- Advertising & Targeted Marketing Strategies
- Campaign Optimization
- Content Creation
- Others (Streamlining Content Production, Dynamic Ad Insertion)
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Telecommunications
- Real-Time Network Monitoring
- Automated Diagnostics & Optimization
- Automated Network Analysis
- Network Planning
- Others (Customer Experience Enhancement, Telecom Revenue Assurance)
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Government & Public Sector
- Law Enforcement & Public Safety
- Real-Time Surveillance & Security
- Real-Time Intelligence Analysis
- Emergency Response Optimization
- Others (Citizen Services, Smart City Management)
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Manufacturing
- Production Planning & Scheduling
- Fault Prediction & Predictive Maintenance
- Optimizing Product Quality
- Monitoring Product Lines
- Demand Forecasting & Inventory Management
- Others (Optimizing Warranty Analysis, Smart Manufacturing)
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Energy & Utilities
- Real-Time Grid Monitoring & Management
- Energy Optimization
- Energy Trading
- Grid & Asset Performance Optimization
- Others (Demand Response & Load Management, Optimizing Maintenance Schedules)
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Transportation & Logistics
- Real-Time Vehicle Tracking
- Route Optimization & Fuel Efficiency
- Fleet Management
- Driver Performance Monitoring
- Others (Transportation Asset Maintenance, Flight Operations Optimization)
- Other Verticals (Education, And Travel & Hospitality)
By Region:
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North America
- US
- Canada
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Europe
- UK
- France
- Germany
- Italy
- Spain
- Rest of Europe
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Asia Pacific
- China
- Japan
- India
- South Korea
- ANZ
- Singapore
- Rest of Asia Pacific
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Middle East & Africa
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Middle East
- Saudi Arabia
- UAE
- Qatar
- Turkey
- Rest of the Middle East
- Africa
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Middle East
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Latin America
- Brazil
- Mexico
- Argentina
- Rest of Latin America
Recent Developments:
- In July 2024, IBM acquired StreamSets, a leader in real-time data integration, to enhance its capabilities in data integration and observability. This acquisition will allow IBM customers to access and analyze data more effectively, with advancements in pipeline observability, automated data drift detection, and end-to-end data lineage. The integration will bolster IBM’s solutions for hybrid and multi-cloud environments.
- In April 2024, SAS Institute and AWS deepened their partnership by expanding SAS-hosted Managed Services to the AWS platform and launching the SAS Viya Workbench on the AWS Marketplace. This collaboration enhances streaming analytics capabilities, allowing users to manage and derive insights from extensive machine learning models in real time, as demonstrated by Georgia-Pacific’s use of these technologies for high-performance AI development.
- In April 2024, Informatica and Google Cloud expanded their partnership by launching an extension that integrates Informatica's data management capabilities with Google Cloud's platform. This collaboration focuses on enhancing trusted customer data analytics and enterprise AI applications, with an emphasis on streaming analytics to provide real-time insights and more responsive data-driven decisions.
- In January 2024, Microsoft announced enhancements to Azure Stream Analytics' No-Code Editor, including advanced visualization, simplified query creation, and enhanced debugging tools. The update also broadens connectivity to support a wider range of data sources and destinations, aiming to deliver a more intuitive and user-friendly experience for both novice and experienced users.
- In September 2023, IBM partnered with Cloudera to enhance real-time data movement and streaming analytics using Apache Kafka. This partnership aims to accelerate data-driven decision-making by integrating IBM's AI solutions with Cloudera's enterprise-grade data platform, benefiting customers with faster data pipeline development, improved cloud migration, and secure, trusted data across hybrid environments.
Frequently Asked Questions (FAQ):
What is streaming analytics?
Streaming analytics refers to the real-time processing and analysis of continuous data streams from various sources. Streaming analytics allows for instant insights and quick responses to constantly changing data, in contrast to the slow processing and large data sizes of traditional batch processing. This technique is essential in different sectors requiring rapid responses, as making timely decisions is crucial. Through the utilization of streaming analytics, businesses can identify trends, transmit alerts, and optimize processes, resulting in improved effectiveness and timely adaptation to dynamic circumstances in real-time environments.
Which region is estimated to hold the highest share in the streaming analytics market?
North America commands the largest share of the streaming analytics market due to its strong economic infrastructure, high consumer spending power, and rapid technological advancements. The region's advanced IT capabilities and extensive adoption of streaming analytics across industries further bolster its market dominance and growth prospects.
Which key verticals adopt streaming analytics software and services?
Key verticals adopting streaming analytics software and services include BFSI, retail & e-commerce, healthcare & life sciences, media & entertainment, telecommunications, government & public sector, manufacturing, energy & utilities, transportation & logistics, and other verticals.
What are the key drivers of the streaming analytics market?
The key market drivers for the streaming analytics market are rising demand for statistical computation and analysis of moving data streams, integration of edge computing to enhance real-time data processing, and rising demand for hyper-personalized customer interactions.
Who are the key vendors in the streaming analytics market?
The key vendors in the global streaming analytics market include 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), and GridGain Systems (US). .
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The research study for the streaming analytics market involved extensive secondary sources, directories, and several journals. Primary sources were mainly industry experts from the core and related industries, preferred streaming analytics software providers, third-party service providers, consulting service providers, end users, and other commercial enterprises. In-depth interviews with primary respondents, including key industry participants and subject matter experts, were conducted to obtain and verify critical qualitative and quantitative information and assess the market’s prospects.
Secondary Research
The market size of companies offering streaming analytics software and services was determined based on secondary data from paid and unpaid sources. It was also arrived at by analyzing the product portfolios of major companies and rating the companies based on their performance and quality.
In the secondary research process, various sources were referred to for identifying and collecting information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers, journals, and certified publications; and articles from recognized authors, directories, and databases. The data was also collected from other secondary sources, such as journals, government websites, blogs, and vendor websites. Additionally, streaming analytics spending of various countries was extracted from the respective sources. Secondary research was mainly used to obtain key information related to the industry’s value chain and supply chain to identify key players based on software, services, market classification, and segmentation according to offerings of major players, industry trends related to offerings, applications, vertical, and region, and key developments from both market- and technology-oriented perspectives.
Primary Research
In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief Experience Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and streaming analytics expertise; related key executives from streaming analytics software vendors, System Integrators (SIs), professional service providers, and industry associations; and key opinion leaders.
Primary interviews were conducted to gather insights, such as market statistics, revenue data collected from software and services, market breakups, market size estimations, market forecasts, and data triangulation. Primary research also helped understand various trends related to technologies, applications, deployments, and regions. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Strategy Officers (CSOs), and end users using streaming analytics, were interviewed to understand the buyer’s perspective on suppliers, products, service providers, and their current usage of streaming analytics software and services which would impact the overall streaming analytics market.
The following is the breakup of primary profiles:
Market Size Estimation
Multiple approaches were adopted for estimating and forecasting the streaming analytics market. The first approach estimates market size by summating companies’ revenue generated by selling software and services.
Market Size Estimation Methodology-Top-down approach
In the top-down approach, an exhaustive list of all the vendors offering software and services in the streaming analytics market was prepared. The revenue contribution of the market vendors was estimated through annual reports, press releases, funding, investor presentations, paid databases, and primary interviews. Each vendor’s offerings were evaluated based on the breadth of offering, application, vertical, and region. The aggregate of all the companies’ revenue was extrapolated to reach the overall market size. Each subsegment was studied and analyzed for its global market size and regional penetration. The markets were triangulated through both primary and secondary research. The primary procedure included extensive interviews for key insights from industry leaders, such as CIOs, CEOs, VPs, directors, and marketing executives. The market numbers were further triangulated with the existing MarketsandMarkets repository for validation.
Market Size Estimation Methodology-Bottom-up approach
The bottom-up approach identified the adoption rate of streaming analytics offerings among different end users in key countries, with their regions contributing the most to the market share. For cross-validation, the adoption of streaming analytics software and services among industries, along with different use cases concerning their regions, was identified and extrapolated. Use cases identified in the different areas were given weightage for the market size calculation.
Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the streaming analytics market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major streaming analytics software providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primaries, the exact values of the overall streaming analytics market size and segments’ size were determined and confirmed using the study.
Top-down and Bottom-up approaches
Data Triangulation
The market was split into several segments and subsegments after arriving at the overall market size using the market size estimation processes as explained above. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Market Definition
According to SoftwareAG, Streaming analytics involves the continuous processing and analysis of live, rapidly moving data from diverse sources, such as Internet of Things (IoT) devices, to generate alerts and automate actions. By analyzing data in real time, it reduces the need for long-term data storage. This approach is crucial for enterprises seeking to derive immediate insights from large and continuously growing volumes of data. As data streams increase, streaming analytics allows businesses to analyze and integrate information in real-time from IoT gateways, sensors, MES, and ERP systems, among other sources.
MarketsandMarkets defines streaming analytics as the real-time processing and analysis of continuous data streams from various sources such as IoT devices, social media, and transactional systems. Streaming analytics allows for instant insights and quick responses to constantly changing data, in contrast to the slow processing and large data sizes of traditional batch processing. This technique is essential in different sectors requiring rapid responses, as making timely decisions is crucial. Through the utilization of streaming analytics, businesses can identify trends, transmit alerts, and optimize processes, resulting in improved effectiveness and timely adaptation to dynamic circumstances in real-time environments.
Stakeholders
- Streaming analytics software developers
- Streaming analytics service vendors
- Cloud service providers
- Consulting service providers
- Enterprise end users
- Distributors and Value-added Resellers (VARs)
- Government agencies
- Independent Software Vendors (ISV)
- Managed service providers
- System Integrators (SIs)/migration service providers
- Technology providers
Report Objectives
- To define, describe, and predict the streaming analytics market by Offering, Application, Processing Type, Data Type, Vertical, and Region.
- To describe and forecast the streaming analytics market, in terms of value, by region—North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
- To provide detailed information regarding major factors influencing the market growth (drivers, restraints, opportunities, and challenges)
- To strategically analyze micro markets with respect to individual growth trends, prospects, and contributions to the overall streaming analytics market
- To profile key players and comprehensively analyze their market positions in terms of ranking and core competencies, along with detailing the competitive landscape for market leaders
- To analyze competitive developments such as joint ventures, mergers and acquisitions, product developments, and ongoing research and development (R&D) in the streaming analytics market
- To provide the illustrative segmentation, analysis, and projection of the main regional markets
Available Customizations
With the given market data, MarketsandMarkets offers customizations per the company’s specific needs. The following customization options are available for the report:
Product Analysis
- The product matrix provides a detailed comparison of the product portfolio of each company.
Geographic Analysis as per Feasibility
- Further breakup of the North American streaming analytics market
- Further breakup of the European streaming analytics market
- Further breakup of the Asia Pacific streaming analytics market
- Further breakup of the Middle East & Africa streaming analytics market
- Further breakup of the Latin America streaming analytics market
Company Information
- Detailed analysis and profiling of additional market players (up to five)
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