Extracting IoT data (sensors and log data, for example) for analysis typically requires a heavy investment in custom development and DevOps. And using machine and sensor data for real time analytics requires not just that the data be continuously delivered to a centralized data hub – but also that it be correlated with data from other sources (including ERPs and inventory management systems).
Equalum integrates directly with both IoT control systems and enterprise applications (like SAP and Salesforce) to stream data to real-time analytics environments – enabling teams to optimize predictive maintenance, production levels, and industrial processes.
Breakthrough use of CDC creates minimal system strain on underlying data sources.
Leveraging a Spark and Kafka foundation; Equalum supports streaming between any number of sources and targets in real-time.
No development required; best-in-class security, monitoring, fault tolerance, and availability without a single line of code.
A Fortune 500 oil and natural gas exploration company struggled with previous data ingestion processes with 10 minutes latency at best, creating big operational and business risks. Developing additional data ingestion processes was very time consuming with hundreds being added every quarter.
Equalum was brought in to stream drilling rigs data, approximately 20,000 events/second with latency of 1 second from Oracle and other sources to a data analytics environment – powering real-time analytics for drill site optimization.
Software Engineer Specialist, Oil & Gas Company