Splunk User Behavior Analytics and Lumu are competing products in the cybersecurity field. Lumu appears to have an edge due to its innovative features, despite Splunk User Behavior Analytics being favored for pricing and support.
Features: Splunk User Behavior Analytics specializes in identifying insider threats with anomaly detection and forensic analysis. It provides comprehensive indexing and powerful search capabilities and supports integration with other cybersecurity tools. Lumu excels in enhancing threat intelligence by continuous traffic monitoring to spot compromised assets, offers an easy-to-use interface with minimal alert fatigue, and provides an effective real-time detection system.
Room for Improvement: Splunk User Behavior Analytics could improve by reducing its setup complexity, enhancing user interface simplicity, and offering more cost-effective pricing options. Lumu may benefit from expanding its feature set to cover broader threat scenarios, offering more detailed analytics dashboards, and improving integration with additional third-party tools.
Ease of Deployment and Customer Service: Splunk requires significant integration and configuration effort but is supported by dedicated teams. Lumu provides a streamlined deployment model with minimal setup time and is praised for responsive support that efficiently resolves issues.
Pricing and ROI: Splunk User Behavior Analytics demands higher initial setup costs, considered justified by long-term ROI through scalability and insights. Lumu offers a cost-effective setup with reports of strong ROI due to rapid threat mitigation and lower operational overhead, making it potentially better value with its cost-efficiency in delivering security outcomes.
Lumu Technologies is a cyber-security company that illuminates threats, attacks, and adversaries affecting enterprises worldwide. Using actionable intelligence, Lumu provides a radical way to secure networks by enhancing and augmenting existing defense capabilities established over the past 25 years.
Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.
We monitor all Intrusion Detection and Prevention Software (IDPS) reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.