Owing to the rapid increase in innovation in today’s highly competitive business environments, agile digital organizations require capabilities to quickly respond to new market trends, customer behaviors, and environmental patterns. WSO2 Stream Processor, with its use of big data, streaming, and historical and predictive analysis, allows organizations to gain a competitive edge. It allows businesses to analyze large data streams, react to changes in real-time, predict trends, and even open up new, domain-specific avenues for entirely new services and products.
As validation of WSO2’s strategy to deliver an open source, cloud native, and lightweight stream processing product that can easily scale up to handle large event rates, WSO2 Stream Processor was recently listed as a Representative Vendor in Gartner’s Market Guide for Event Stream Processing1. The guide looks at vendors with cloud and on-premises offerings, as well as proprietary and open-source products.
Gartner defines event stream processing platforms as, “software systems that perform real-time or near-real-time calculations on event data ‘in motion.' The input is one or more event streams containing data about customer orders, insurance claims, bank deposits/withdrawals, tweets, Facebook postings, emails, financial or other markets, or sensor data from physical assets such as vehicles, mobile devices or machines.” The report identifies two sub-segments in the market: stream analytics event stream processing (ESP) offerings and stream data integration ESP offerings.
According to the report, “Increasingly demanding consumers and intensifying digital competition are pushing analytics from transactional to continuous. To achieve the necessary continuous intelligence, data and analytics leaders must understand and master the event stream processing market.”
WSO2 Stream Processor helps agile digital organizations accelerate time to insight from data by providing users more autonomy in managing tools. It is an open source, cloud native, and lightweight stream processing platform that understands streaming SQL queries in order to capture, analyze, process and act on events in real time. This facilitates real-time streaming analytics and streaming data integration. With the product’s simple deployment and its ability to rapidly adapt to changes, enterprises can go to market faster and achieve greater ROI. It comprises many features that enable enterprises to build streaming analytics capabilities and derive meaningful insights out of an organization's data.
Unlike other offerings, it is the only stream processor that provides high availability and 100K+ throughput with just two nodes and scales to 30+ billion events per day with its Kafka-based distributed deployment. The Siddhi Streaming SQL language also enables users to adapt to the market faster with quicker development times. The product can be utilized as a lightweight deployment, with the ability to handle large event rates, sophisticated and complex streaming operators, or out-of-order message processing. It can also process real-time queries that span from seconds to years. With its rich and agile development experience, it also provides business users more autonomy in managing tools.
1Gartner, Inc. "Market Guide for Event Stream Processing” by Nick Heudecker and W. Roy Schulte, June 15, 2018.