Having access to timely data regardless of where it resides is a must-have to run your business operations smoothly. Striim offers the foundation for a modern, streaming data architecture, and easily integrates your structured, semi-structured and unstructured data, on-premises or in the cloud, with sub-second latency. With Striim, you can easily adopt a next-generation infrastructure by integrating data across Cloud, Big Data, and IoT devices without getting locked in to a single topology.
Striim combines non-intrusive, real-time change data capture capabilities with in-flight data processing to deliver timely and enriched data to the rest of the enterprise. It is an end-to-end, enterprise-grade platform with built-in stream analytics and data visualization, and delivers real-time insights while moving the data with sub-second latency. Striim provides an intuitive development experience with wizard-based user interface and speeds time-to-deployment with pre-built data pipelines. Using an SQL-like language, it is familiar to both business analysts and developers. With Striim, you adopt a future-proof, smart data architecture for accelerated innovation.
HP Enterprise uses Striim to accelerate its order management process. Historically, the company had no visibility into the order process for up to 2 days after an order was placed. Striim enables real-time data integration from ERP, MDM, and credit scoring systems into Hortonworks, Kafka, and HPE NonStop environments to enable fast order processing with access to real-time data. Now HPE has real-time visibility to order management activities and can check customer creditworthiness in real time to expedite the process.
Gained visibility into the order process from 1- 2 days to instantaneous via real-time data integration
Expedited the order processing for its customers with immediate customer data validation and fast credit check
Adopted a modern, future-ready streaming data architecture that supports fast innovation and improved customer
Striim ingests real-time data from a wide variety of sources including databases, log files, IoT devices, message queues, for different data types such as JSON, XML, delimited, binary, free text, change records. For transactional databases, it uses non-intrusive change data capture (CDC). Striim runs continuous queries to filter, transform, aggregate, enrich, and analyze the data-in-motion before delivering it to virtually any target with sub-second latency. If desired, Striim can process the data in batch as well.