The insideBIGDATA Guide to Streaming Analytics is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting new area of technology. Many enterprises find themselves at a key inflection point in the big data timeline with respect to streaming analytics technology. There is a huge opportunity for direct financial and market growth for enterprises by leveraging streaming analytics. Streaming analytics deployments are being engaged by companies in a broad variety of different use cases. The vendor and technology landscape is complex and numerous open source options are mushrooming. It’s important to choose a platform that will supply a proven and pre-integrated, performance-tuned stack, ease of use, enterprise-class reliability and flexibility to protect the enterprise from rapid technology changes. Maybe the most important reason to evaluate this technology now is that a company’s competitors are very likely implementing enterprise-wide real-time streaming analytics right now and may soon gain significant advantages in customer perception & market-share. The complete insideBIGDATA Guide to Streaming Analytics is available for download from the insideBIGDATA White Paper Library.
StreamAnalytix is a state-of-the-art streaming analytics platform based on a best-of-breed open source technology stack. StreamAnalytix is a horizontal product for comprehensive dataingestionacross industry verticals. It is developed on an enterprise-grade scale with open source components including Apache Kafka, Apache Storm and Apache Spark while also incorporating the popular Hadoop and NoSQL platforms into its structure. The solution provides all required components for streaming app-development not normally found in one place, all brought together under this platform combined with an extremely friendly UI.
A key benefit of StreamAnalytix is the multi-engine abstracted architecture which enables alternative streaming engines underneath—supporting Spark Streaming for rapid and easy development of realtime streaming analytics applications in addition to original support for Apache Storm. Being able to choose among multiple streaming engines means you can take the risk out of being constrained with a single engine. With a multiengine streaming analytics platform, you can do Storm streaming pipelines and Spark streaming pipelines and interconnect them—using the best engine for the best use case based on the optimal architecture. When new engines become widely accepted in the future they can be rolled into this multi-engine platform.
The following is an overview of the product and its enterprise-grade, multi-engine open source based platform:
Open source technology
StreamAnalytix is built on Apache Storm and Apache Spark (open source distributed real-time computation systems) and is therefore able to leverage the numerous upgrades, improvements and flow of innovation that are foundational to the global Open Source movement.
Spark streaming includes a rich array of drag-and-drop Spark data transformations, Spark SQL support, and built-in operators for predictive models with inline model-test feature.
Versatility and comprehensiveness
StreamAnalytix is a “horizontal” product for comprehensive high-speed data-ingestion across industry verticals. Its IDE development environment offers a palette of applications based on customer requirements. Multiple components can be dragged and dropped into a smart dash-board in order to create a customized work-sphere. The visual pipeline designer can be used to create, configure and administer complex real-time data pipelines.
The platform’s architecture incorporates an abstraction layer beneath the application definition interface. This innovative setup enables automatic selection of the ideal streaming engine while also allowing concurrent use of several engines.
Built on Apache Storm, Apache Spark, Kafka and Hadoop, the StreamAnalytix platform is seamlessly compatible with all Hadoop distributions and vendors. This enables easy ingestion, processing, analysis, storage and visualization of streaming data from any input data source, proactively boosting split-second decision making.
“Low latency” capability and flexible scalability
The platform’s ability to ingest high-speed streaming data with very low, sub-second latencies makes it ideal for use cases which warrant split-second response, such as flight-alerts or critical control of risk factors prevalent in complex manufacturing environments. Any fast-ingest data store can be used.
Intricate robust analytics
StreamAnalytix offers a wide collection of built-in data-processing operators. These operators enable high-speed data ingestion and processing in terms of complex correlations, multiple aggregation functions, statistical models and window aggregates. For rapid application development, it is possible to port predictive analytics and machine learning models built in SAS or R via PMML onto real-time data.
Detailed data visualization
StreamAnalytix provides comprehensive support for 360-degree real-time data visualization. This means the system delivers incoming data streams instantaneously in the form of appropriate charts and dashboards.