Gurucul UEBA and LogRhythm UEBA are prominent competitors in the user and entity behavior analytics category. Data comparisons suggest Gurucul UEBA is more appealing for budget-conscious buyers due to its cost benefits, while LogRhythm UEBA justifies a higher price with its robust feature set.
Features: Gurucul UEBA is known for its advanced machine learning analytics, integration with diverse data sources, and customization capabilities. LogRhythm UEBA stands out with comprehensive security analytics, incident response capabilities, and extensive native features that lessen configuration needs.
Ease of Deployment and Customer Service: LogRhythm UEBA benefits from a polished deployment model with strong resources and support, facilitating setup and management. Gurucul UEBA, though more flexible, requires more manual configuration. Gurucul's customer service is noted for responsiveness and adaptability, while LogRhythm provides a structured support environment.
Pricing and ROI: Gurucul UEBA's competitive pricing appeals to those focused on ROI, with lower setup costs offering an accessible entry. LogRhythm UEBA's initial investment is higher but offers ROI through advanced threat detection, deemed worth the added expense due to its comprehensive features.
Threats are a moving target. Determined and persistent threat actors purposely stretch out their activity across weeks or even months, especially when most SIEM and XDR solutions are incapable of piecing together events across time. Even worse, is that these solutions primarily use rule-based Machine Learning, which is essentially pattern matching. This makes them especially ineffective in detecting new attacks and/or variants, which are highly successful in breaching organizations. Discover how Gurucul UEBA security can help your enterprise.
LogRhythm UEBA enables your security team to quickly and effectively detect, respond to, and neutralize both known and unknown threats. Providing evidence-based starting points for investigation, it employs a combination of scenario analytics techniques (e.g., statistical analysis, rate analysis, trend analysis, advanced correlation), and both supervised and unsupervised machine learning (ML).
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