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The availability of business insights and information is a significant factor for competitive advantage in modern businesses. This allows busienss owners to make decisions in real-time. Real-time stream processing and streaming analytics is the technology that makes this a reality.

The first generation Stream Processors pose several challenges.

Complex Code
Obese Deployments 
Slow to change 
Even standard operators such as time windows and temporal patterns require users to write complex code. They need a lot of time and lots of skills requiring too much time in upkeep, which most organizations cannot afford.Even a basic highly available deployment requires 5+ servers. Such deployments are complex, take time to setup, and are expensive to maintain.The fast pace of changes forces organizations to adapt. However, the complexity of the code, the lack of visibility of the processing flow, and the lack of tooling in Stream Processors stall the change lifecycle.

WSO2 Stream Processor (SP) is a 100% open source streaming analytics and stream processing solution that allows you to build and deploy applications that collect, analyze, and present data in real-time.

  • Collects events from multiple event sources using various data formats.

  • Preprocesses by deploying at the edge.

  • Processes stream of events in real-time using Streaming SQL queries.

  • Summarizes and correlates events in memory and by integrating with data stores.

  • Notifies interesting event occurrences via alerts and service calls.

  • Visualizes the summarizations via dashboard.

It has the following capabilities:

  • Process millions of events per second in real-time
    WSO2 SP is the sole analytics product in the market that facilitates high-performance analytics with only 2 nodes (minimum HA). It can process approximately 100,000 events per second with the ability to scale beyond with Apache Kafka.

  • Be updated at all times with incremental analytics
    WSO2 SP replaces periodic batch operations with out-of-the-box long-running incremental processing to achieve updated analysis at each arrival of data.

  • Adapt to the market faster with shortened development time
    Provides analysis in a specialized, easy-to-use, Siddhi Streaming SQL language using the state-of-the-art IDE, providing agile development experience with smart editing, simulation and debugging capabilities.

  • Investigate the past, predict the future
    Gain insights using past performances, build pre-trained and online machine learning models, and perform real-time predictions to drive business planning.

  • Enable insights into all your systems
    Work out-of-the-box with popular data formats, transport protocols and connect to over 100 legacy and cloud services via connectors and agents.

  • Enable managers to manage their business rules and visualize output
    Empower business users to create and dynamically deploy business rules through easy to use graphical UI, and let them make better decisions utilizing real-time dashboards.

  • Build smarter devices with edge analytics
    Make devices smarter by deploying WSO2 Siddhi (<2MB) for localized data analytics, and let centralized deployments such as IoT analytics handle a massive amount of data by filtering and summarising at the edge.

  • Build an event-driven architecture using streaming data integration
    Build information-rich streams by connecting to diverse data streams, letting organizations to get a better overall understanding of their data in real-time, and to build control flows.

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