The global streaming analytics market size was valued at USD 12,607 million in 2021. It is expected to reach USD 107588.62 million by 2030, growing at a CAGR of 26.90 % during the forecast period (2022–2030).
Statistical computation and analysis of moving data streams are provided continuously by streaming analytics. It enables businesses to perform real-time analytics calculations on data streaming from websites, devices, sensors, social media, and applications.
It also reduces the complexity of stream processing systems by processing millions and tens of millions of events per second using a straightforward SQL variant. Streaming analytics allows businesses to find new sources of income and business opportunities, which increases new clients, revenue, and customer satisfaction. As streaming analytics help to improve accuracy and reliability and streamline the expression of complex business outlines and scenarios, there is a clear trend toward integrating them with machine learning, predictive analytics, and rules engines.
|Market Size||USD 107588.62 million by 2030|
|Fastest Growing Market||Europe|
|Largest Market||North America|
|Report Coverage||Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends|
Quick data processing increased competitive pressure, the real-time ability to act on business opportunities and the demand for contextual and time-relevant customer experiences drive the shift toward real-time analytics. Streaming analytics vendors offer customer 360 frameworks, anomaly detection, churn analytics, recommendation engines, and predictive maintenance. Organizations are refocusing on gathering information about streaming events to improve operational responsiveness and organizational effectiveness. Streaming analytics solutions give businesses rich context, lower infrastructure costs, increased operational efficiencies, and faster insights and actions. All these factors should encourage end users to adopt streaming analytics software, fueling market growth.
The development of artificial intelligence (AI), big data, the Internet of Things, and cloud computing has led to new opportunities to glean insights from streaming data. Connected cameras, sensors, and other devices produce massive amounts of data. Without data analytics, this data is useless. Streaming analytics discovers new information through batch processing and offline analysis. Continuous data analysis requires streaming analytics tools that update insights every few seconds or milliseconds. Businesses use AI to combine historical data with current business processes to create precise predictive models. Using streaming analytics software, companies can extract patterns from real-time data and identify anomalies. Cutting-edge technologies will increase demand for streaming analytics software, driving market growth.
Manufacturers in Asia-Pacific have implemented IoT systems and plan to expand their use to gain a competitive advantage. IoT could boost manufacturing productivity by USD 216–627 billion. Manufacturers will gain a real-time end-to-end production view by integrating sensors into machines and factory systems. Using IIoT (Industrial Internet of Things) sensor data, they can address blockages, reduce waste, and improve operational efficiencies. Massive volumes and varieties of IIoT data require streaming analytics software because the data will have different standards, formats, and protocols, which can be challenging for manufacturers. The success of IoT deployments in manufacturing depends on manufacturers' ability to gain insights from high-volume data. Streaming analytics provides a real-time, scalable, end-to-end streaming data platform that ingests and analyzes data to deliver actionable insights, helping manufacturers overcome IIoT's complexities and driving its adoption.
Organizations must efficiently handle enormous volumes of data, which is an expensive process due to increased competition among market players and the impending implementation of new data privacy and security regulations. Consequently, the storage, processing, and accessing of this data presents a possible challenge for firms that utilize streaming analytics. Evaluation of legacy infrastructure and assessment of new technology have become necessities for organizations, primarily to gain competitive advantage and compliance, as the demand for Big Data exceeds the limitations of traditional relational databases. Since the modernization of the legacy system is necessary for integrating big data into it, integrating big data with legacy infrastructure becomes difficult. Companies will find it challenging to replace or eliminate the current legacy systems because they are their main assets.
Streaming analytics market growth may be negatively impacted by data security or privacy concerns, strict data security regulations that vary by region, and other factors. Financial institutions, hospitals, and other businesses handle enormous volumes of sensitive data, including debit/credit card and personally identifiable information (PII). Depending on customers' location, this information may be subject to strict compliance protocols like the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Payment Card Industry Data Security Standard (PCI DSS), and other laws and regulations. Accessing these real-time data would be challenging, which limits market expansion.
Streaming analytics vendors are creating new data integration and high event-streaming analytics capabilities to outperform rivals and broaden the range of commercial applications. As a result, these players are implementing several strategies, including introducing new products and collaborations with tech start-ups to create creative solutions, which are anticipated to present lucrative opportunities for market expansion.
For example, Yellowbrick Data, a U.S. database company that offers SQL analytics and parallel processing data warehouse products, partnered with Striim in June 2020 to speed up the deployment of data streaming applications and help businesses gain quicker and more accurate insights. Thus, it is anticipated that several strategies used by major market players to widen their customer base and offer complete product lines will present lucrative market opportunities.
By region, the global streaming analytics market is segmented into North America, Europe, Asia-Pacific, and LAMEA.
North America is the most significant market shareholder and is expected to grow at a CAGR of 23.5% during the forecast period. The US and Canada make up the North American streaming analytics market. Additionally, as more organizations struggle to interact with customers in the moment and in a relevant, meaningful way due to the availability of various data sources at the on-premises, edge, and in multiple clouds, the adoption of artificial intelligence (AI)-powered streaming analytics solutions is rising. The region has seen a high surge in the adoption of cloud technologies, which supports the market's expansion. Further, factors like the rising trend of automation in the retail and healthcare sectors, the high Internet of Things (IoT) adoption rate to improve operations, and the surge in cloud technology adoption in the North American region are expected to accelerate the market's growth.
Europe is expected to grow at a CAGR of 26.3%, generating USD 23,349.44 million during the forecast period. The UK, Germany, France, and the rest of Europe make up the Europe streaming analytics market. Due to factors like ease of conducting business and dependable access to pertinent markets and infrastructure, international corporations are investing heavily in emerging and traditional analytics tools in Europe as part of data-driven business initiatives. The data-driven investments in this area are anticipated to positively affect the market expansion for streaming analytics.
The Asia-Pacific streaming analytics market includes China, India, Japan, and other countries. Streaming analytics solutions will analyze real-time IoT data streams to improve user experience and productivity. The Asia-Pacific region is expected to undergo the highest growth rate in the coming years due to increased technology spending in China, India, and Japan and a rise in demand for affordable analytical solutions among SMBs.
Latin America, the Middle East, and Africa are LAMEA's streaming analytics markets. Massive data generation in almost every industry vertical forces companies to update their systems to make more intelligent real-time decisions, driving market growth. The increasing adoption of streaming analytics in LAMEA has fueled the market growth.
The global streaming analytics market is segmented by component, deployment model, organization size, application, and industry vertical.
By component, the global market is segmented into software and service.
The software segment dominates the market and is expected to grow at a CAGR of 25.5% over the forecast period. Streaming analytics software produces analytical calculations on streaming data produced by sensors, websites, social media, devices, applications, and infrastructure systems. Many companies have adopted streaming analytics software to analyze unstructured video, audio, text, geospatial, and IoT sensor data and identify business threats and opportunities. Increased demand for real-time data analytics and higher consumer engagement significantly expand the market.
Training, implementation, and consulting are professional services. Implementation services include scheduling, installing, and configuring solutions, plus a custom program to meet specific needs. Support services include tracking and managing concerns with personalized help and performance development.
By deployment model, the global market into on-premise and cloud.
The cloud segment contributed the most to the market and is expected to grow at a CAGR of 28.6% during the forecast period. The licensing and delivery model for streaming analytics applications uses the cloud, where a service provider hosts the applications and distributes access to their functionality as a service. This deployment model allows the IT team to facilitate real business value to the organization through lower anticipated costs and a better ability to concentrate on innovation and differentiation. To improve operational procedures, boost customer satisfaction, and give executives crucial data points, businesses are increasingly deploying cloud platforms and cutting-edge data processing solutions. This market shift is spurring more investments in real-time analytics to gain deeper insight from real-time data, further fostering the market's expansion.
By organization size, the global market is segmented into large enterprises and small and medium-sized enterprises.
Large enterprises own the highest market share and are expected to grow at a CAGR of 26.1% over the forecast period. Large businesses with more than 500 employees and USD 1 billion in annual revenue are considered in the streaming analytic market. Due to their access to a large volume of data, large businesses are increasingly using streaming analytics. Large companies produce enormous amounts of data through transactions, customer service inquiries, customer orders, sales leads, mobile apps, kiosk activity, social media activity, chat messages, and supply chain updates. They are using real-time analysis pipelines to get insights instantly, which helps them manage their user base and products more effectively.
The streaming analytics market considers small and medium businesses with fewer than 500 employees and USD1 billion in annual revenue. Demand for data analytics solutions and SMB awareness of streaming analytics is growing in the market. Small and medium-sized businesses are expected to increase the most due to their rapid adoption of cloud-based streaming analytics services across industry verticals.
By application, global market is segmented into fraud detection, predictive asset management, risk management, network management and optimization, sales and marketing, supply chain management, and location intelligence.
The fraud detection segment is the largest contributor and is expected to grow at a CAGR of 21.9% during the forecast period. In several industries, including the BFSI and retail and e-commerce, fraudulent or false transactions can cost millions annually. Identity theft and lost credit cards continue to rank among the top concerns for many industries, making a deadline for their resolution necessary. Streaming analytics software performs analyses of real-time data by utilizing continuous queries. As a result, businesses can analyze the data as soon as it is made accessible to them. By creating numerous business opportunities, the company can instantly analyze this data and quickly spot a variety of frauds.
Streaming analytics helps manage multiple data sources and improve ads. These include web traffic, ad inventory, click logs, and customer demographic and behavioral data. These insights improve pricing strategies, audience targeting, conversion rates, and campaign ROI and create new revenue opportunities. Streaming analytics is used to get social media opinions and digital marketing results, improving the next campaign and boosting conversion rates.
By industry vertical, the global market is segmented into BFSI, IT and telecom, manufacturing, government, retail and e-commerce, media and entertainment, health care, and energy and utilities.
The IT and telecom segment owns the highest market share and is expected to grow at a CAGR of 17.7% during the forecast period. The IT and telecom industries can now use their device, network, call records (CDRs), and subscriber data to extract real-time, actionable intelligence. Communication service providers are processing data in real-time using streaming analytics by utilizing data stream processing, which merges flowing extract, transform, and load (ETL) streams of aggregated data straight into data warehouses for more immediate business reporting. This results in real-time alerts, automated actions and updates, and more accurate business reporting.
The raw data generated by market activity, online trading, network data, monitoring of financial transactions, social media, as well as stored data like call logs, credit card history, demographics, and performance reports, is combined by streaming analytics. By stream analytics, BFSI businesses can identify and foresee security threats in real time, stop fraud, boost customer acquisition and retention, uphold compliance standards, and eliminate expensive network failures.