Based on a recent conversation between Steve Wilkes, founder and CTO of Striim, and Dataversity, the publication published a great piece that takes a hard look at some of the most common industry struggles in dealing with real-time data, and how the Striim platform is uniquely engineered to help organizations adopt a modern data architecture through streaming integration.
The article sets the stage by explaining some of the demands that data architects face today in gaining value from real-time data, from the variety of sources generating data to the number of open source environments and frameworks enterprise companies have the option of working with its data in (Hadoop, Kafka, cloud, edge, etc.). Because of this, developing a solution that works cohesively based on so many factors is difficult and expensive to do. These factors include what to use for ingestion, processing and analytics, delivery, and alerting and visualization.
Luckily, the Striim platform was built to be an end-to-end, enterprise grade solution that is scalable, reliable, and secure to effectively handle each and every aspect of these considerations.
The article highlights Striim’s real-time data integration capabilities, which is one of the most important elements when adopting a modern data architecture. As mentioned earlier, organizations have so many options and often have their data in different digital frameworks. Because of this, interoperability becomes a problem due to each environment’s unique digital makeup. Striim’s goal is to not keep companies bogged down because of “plumbing” issues, as quoted by Steve in the piece:
“We want to enable developers to focus on solving business problems and not plumbing problems,” said Wilkes. “We provide the plumbing, the data movement and processing capabilities, and they plug in their own value adds – the business logic – to move the business forward.”
Striim enables enterprise companies to not only ingest data from multiple sources, but also provides built-in stream processing, analytics, and visualization capabilities. Striim enables data correlation to join together multiple streams, as well as complex event processing to spot anomalies and patterns within the data, so that companies can make critical business decisions while the data is still relevant. Because the data is streaming, everything is updated in real time and displayed via Striim dashboards, where alerts and triggers can be set up to monitor data accordingly.
With an all-in-one solution, companies can save valuable time and money by adopting Striim’s proprietary solution instead of building on their own.
To learn more about the Striim platform, as well as how one customer has been using complex event processing to alert on potential security threats, read the article on Dataversity, “Streamlining Real-Time Data Integration and Analytics: The Struggle is Over.”
