Streaming Graph Use Cases

A cyber security client launched a new AWS CloudTrail log security monitoring product in record time.

Find advanced persistent threat (APT) behaviors in large event stream volumes and across extended time periods.

Quine and Novelty Detector make it possible for modern threat hunting to focus on real time behavior analysis.

Digital twins need real-time event processing to truly reflect ever changing system state.

Combine logs from multiple services to understand system performance issues and their root causes.

Real-time ETL on streaming data, especially when data is received from multiple sources, requires new tools to accommodate out-of-order data arrival and entity resolution, while operating at the scale of todays cloud, CDN and application event volumes.

Video delivery monitoring is hard. Logs come from multiple sources with high dimensionality and cardinality, at scale. Real-time analysis requires new tools.

Financial fraud detection typically relies on analysis of event volumes and transaction size by user/device bypassing much of the categorical data that defines user/device behavior patterns in a much more complete context.

Low frequency authentication attacks, such as password spraying and credential stuffing, circumvent real-time authentication application business rules and batch analysis by log analysis/SIEM systems.

Use Quine to detect and trace fraudulent transactions across blockchains in real time.