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The streaming analytics market size is estimated to increase by USD 23.6 billion and grow at a CAGR of 28.89% between 2022 and 2027. Market expansion hinges on various factors, such as the imperative to enhance business efficiency, the rising incorporation of IoT-driven devices, and the escalation in data production coupled with the emergence of big data. Nonetheless, impediments exist that could thwart this growth trajectory. These obstacles encompass the challenge of integrating legacy systems with streaming analytics solutions, apprehensions regarding privacy and security, and obstacles related to deployment that may hinder progression. Despite the promising landscape facilitated by endeavors to bolster operational effectiveness and the proliferation of IoT-enabled technologies, addressing these hurdles is imperative for sustained market advancement. Overcoming these challenges necessitates strategic approaches, robust security measures, and innovative deployment strategies to surmount integration complexities and ensure privacy while harnessing the transformative potential of IoT and big data in driving business growth and competitive advantage.
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This report extensively covers market segmentation by deployment (cloud and on-premise), type (software and services), and geography (North America, APAC, Europe, Middle East and Africa, and South America). It also includes an in-depth analysis of drivers, trends, and challenges. Furthermore, the report includes historic market information from 2017 to 2021.
The market share growth by the cloud segment will be significant during the forecast period. The Streaming Analytics Market encompasses advanced solutions that leverage AI and API to automate the analysis of continuous data streams in real time. These cloud-based Cloud solutions enable businesses to streamline their decision-making processes by providing quick access to big data, ensuring connectivity and integration, and adhering to compliance regulations. The benefits of cloud adoption include improved flexibility, scalability, and real-time visibility, making it an essential tool for various commercial applications.
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The cloud segment was valued at USD 3.70 billion in 2017 and continued to grow until 2021. Businesses can easily integrate these solutions into their existing business logic and processes, enhancing their capabilities with event-streaming analytics. The financial impact of these solutions extends to fraud detection and prevention, as well as direct decisions in sectors like healthcare, where privacy and accessibility are crucial. The ease of use and continuous enhancements make streaming analytics an essential component of digitization and the adoption of emerging technologies.
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North America is estimated to contribute 33% to the growth of the global market during the forecast period. Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
In North America, the market holds significant importance due to the region's status as an early adopter of advanced technology and a leader in generation and consumption. IoT devices and IT infrastructure in large enterprises and SMEs generate vast amounts, necessitating the use of streaming analytics to optimize processes and discover valuable insights in real time. Legacy infrastructure and systems in organizations require modernization and modifications to accommodate real-time processing. Location Intelligence and predictive models are essential to use cases for various sectors, including retail and telecom, to gain a competitive edge. Real-time prediction of production and demand, security breaches, and other metrics are crucial for organizations to respond effectively to real-time events. The scalability and security of on-premises and cloud-based solutions are key considerations for the market's growth. The strategic shift towards advanced technologies, such as AI and virtualization, presents opportunities for startups and tech-mature industries, including IT and telecom, to optimize operations and gain a competitive edge. However, technical drawbacks, such as real-life experience limitations and the need for real-time prediction accuracy, pose challenges to the market's growth.
In today's digital landscape, the market has gained significant traction among both Large Enterprises and Small & Medium Enterprises (SMEs) in various sectors, including Retail. This market's growth can be attributed to the strategic shift towards digitalization and the adoption of emerging technologies such as API, Big Data, IoT (Internet of Things), Artificial Intelligence (AI), and Cloud solutions. Streaming Analytics enables real-time processing and analysis, which is crucial for businesses in production and demand environments.
For instance, in the Retail sector, it can help detect and prevent fraud cases in real-time, ensuring the financial impact is minimized. Legacy systems, however, pose a challenge in implementing Streaming Analytics. To address this, Cloud solutions offer cost-effective and efficient alternatives for connectivity and processing. The integration of Streaming Analytics with these Cloud solutions can lead to significant improvements in operational efficiency and business agility.
Moreover, KPIs (Key Performance Indicators) are crucial for monitoring performance in hybrid and multi-cloud environments, ensuring efficiency and alignment with business objectives. In conclusion, the market is a vital component of the digitalization journey for businesses. Its ability to process and analyze in real-time, coupled with the integration of emerging technologies and Cloud solutions, makes it an essential tool for managing production and demand environments and mitigating risks, such as Fraud cases.
The increasing adoption of IoT-based devices is notably driving market growth. In today's data-driven business landscape, advanced analytics solutions have become essential tools for optimizing costs and increasing revenue. Powered by AI and machine learning, this service enables businesses to process continuous streams in real-time, providing valuable insights for predicting opportunities and challenges. Cloud adoption and cloud solutions have made streaming analytics more accessible and easier to deploy, with API integration allowing seamless data connectivity and accessibility.
In addition, compliance regulations and cyber-attacks necessitate robust security measures, including data privacy and encryption. They offer commercial applications across various industries, including healthcare, finance, and marketing, by automating business processes, enhancing decision-making, and improving brand reputation through real-time fraud detection and event-streaming analytics capabilities. With continuous development and ease of use, streaming analytics is a crucial component of digitalization and the future of business efficiency. Therefore, such factors will positively impact the growth of the global market during the forecast period.
Integration with AI (Artificial Intelligence) and ML (Machine Learning) technologies is an emerging trend in market growth. The market is witnessing a notable trend towards the integration of advanced AI and ML technologies. These technologies are enhancing the capabilities of streaming analytics solutions, enabling more accurate and predictive insights for businesses. By combining AI and ML with streaming analytics, businesses can gain deeper insights into their data, automate processes, and make faster, informed decisions. Cloud solutions and APIs facilitate the integration of these technologies, making them accessible to a wider range of commercial applications.
Moreover, AI and ML can identify patterns in continuous data streams, predict future trends, and automate compliance with regulations. This integration is particularly valuable in sectors such as healthcare and finance, where real-time insights can have a significant impact on business logic and decision-making processes. Additionally, AI and ML can help businesses respond proactively to cyber-attacks and fraud cases, ensuring data privacy and security. Overall, the integration of AI and ML with streaming analytics is a key driver of digitization and digital transformation in various industries. Hence, such factors will positively impact the growth of the global market during the forecast period.
Data privacy and security concerns are major challenges impeding the market growth. In today's data-driven business landscape, the ability to process and analyze large volumes in real time is becoming increasingly crucial. Advanced streaming analytics solutions are gaining popularity as they enable businesses to automate the processing of continuous data streams from various sources. These solutions are particularly beneficial for companies with mainframes and traditional systems, as they can help integrate data into analytics platforms for real-time insights. Cloud adoption and cloud solutions are driving the growth of the market. AI and API integrations are enhancing the capabilities of these solutions, making them more accessible and user-friendly for businesses.
In addition, compliance regulations and cyber-attacks are also pushing businesses to prioritize data privacy and security in their analytics strategies. These solutions offer numerous benefits, including improved decision-making processes, enhanced business logic and processes, and direct customer engagement. They are also valuable in commercial applications such as fraud detection and real-time financial impact analysis. Emerging technologies like healthcare and IoT are also expected to drive the growth of the market in the coming years. Hence, such factors will hinder market growth during the forecast period.
The report includes the adoption lifecycle of the market, covering from the innovator’s stage to the laggard’s stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their growth strategies.
Global Customer Landscape
Market players are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.
Impetus Technologies Inc. - The company offers cloud ops, data ops, and cost engineering. The key offerings of the company include streaming analytics such as one data pipeline platform.
The report also includes detailed analyses of the competitive landscape of the market and information about 15 market companies, including:
Qualitative and quantitative analysis of vendors has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize vendors as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize vendors as dominant, leading, strong, tentative, and weak.
The report forecasts market growth by revenue at global, regional & country levels and provides an analysis of the latest trends and growth opportunities from 2017 to 2027.
In today's data-driven business landscape, Streaming Analytics has emerged as a crucial technology for real-time data processing and analysis. The Streaming Analytics market is witnessing significant growth due to the increasing demand for real-time insights from various industries, including Finance, Healthcare, Retail, and Telecommunications. Apache Kafka and Amazon Kinesis are popular open-source and cloud-based streaming platforms, respectively, that enable real-time data processing using Streaming Analytics. These platforms provide features like data ingestion, processing, and analysis at scale, making them ideal for handling large volumes of data in real-time. Cloudera, Microsoft, and IBM are some of the major players in the Streaming Analytics market, offering comprehensive solutions that include streaming data processing, machine learning, and data visualization.
However, these solutions help businesses gain actionable insights from their data, enabling them to make informed decisions and improve operational efficiency. Moreover, the integration of Streaming Analytics with other big data technologies like Hadoop, Spark, and NoSQL databases provides businesses with a unified data processing and analysis platform. This integration enables seamless data flow between different data processing engines, making it easier for businesses to gain insights from their data in real time. In conclusion, the market is witnessing significant growth due to the increasing demand for real-time data processing and analysis. With the help of platforms like Apache Kafka and Amazon Kinesis, and solutions from major players like Cloudera, Microsoft, and IBM, businesses can gain actionable insights from their data in real-time, enabling them to make informed decisions and improve operational efficiency.
Streaming Analytics Market Scope |
|
Report Coverage |
Details |
Page number |
170 |
Base year |
2022 |
Historic period |
2017-2021 |
Forecast period |
2023-2027 |
Growth momentum & CAGR |
Accelerate at a CAGR of 28.89% |
Market growth 2023-2027 |
USD 23.6 billion |
Market structure |
Fragmented |
YoY growth 2022-2023(%) |
25.79 |
Regional analysis |
North America, APAC, Europe, Middle East and Africa, and South America |
Performing market contribution |
North America at 33% |
Key countries |
US, Canada, China, Japan, and UK |
Competitive landscape |
Leading Vendors, Market Positioning of Vendors, Competitive Strategies, and Industry Risks |
Key companies profiled |
Adobe Inc., Alphabet Inc., Altair Engineering Inc., Amazon.com Inc., Cloudera Inc., Conviva Inc., Coralogix Ltd., Hewlett Packard Enterprise Co., Impetus Technologies Inc., Informatica Inc., Intel Corp., International Business Machines Corp., Microsoft Corp., Mphasis Ltd., Oracle Corp., SAP SE, SAS Institute Inc., Software AG, Striim International Inc., Teradata Corp., and TIBCO Software Inc. |
Market dynamics |
Parent market analysis, Market forecasting, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, Market condition analysis for the forecast period. |
Customization purview |
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1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by Deployment
7 Market Segmentation by Type
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Trends
11 Vendor Landscape
12 Vendor Analysis
13 Appendix
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