Stream IoT data (e.g., machine, sensor and network data) to data warehouses or data lakes, where it can be correlated with legacy application data to fuel real-time analytics.
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 uses Equalum to stream 10,000 events/second with latency of 1 second from drilling rigs to their real-time analytics environment – enabling drill site operators to make timely optimizations.