Security teams should compare security data lakes based on centralized data collection, threat detection, analytics, storage, integrations, scalability, security, automation, compliance, and cost.
- Microsoft Sentinel: Provides cloud-native security analytics, centralized data collection, threat detection, and automated response.
- Splunk: Supports large-scale security data ingestion, search, monitoring, analytics, and threat detection.
- Google Security Operations: Combines security data management, threat detection, investigation, and response capabilities.
- IBM QRadar: Provides security data collection, analytics, threat detection, and security monitoring.
- Elastic Security: Supports centralized security data collection, search, detection rules, analytics, and investigation.
- Amazon Security Lake: Centralizes security data from AWS, cloud, and third-party sources for security analysis.
- Sumo Logic: Provides cloud-based security analytics, centralized log management, monitoring, and threat detection.
- Datadog Security Monitoring: Combines security data collection, monitoring, detection, investigation, and cloud security analytics.
- Exabeam: Provides security data management, behavioral analytics, threat detection, and investigation capabilities.
- CrowdStrike Falcon LogScale: Supports high-volume security data collection, real-time search, analytics, and threat investigation.
Security teams should also compare data ingestion, storage capacity, detection capabilities, analytics, integrations, threat intelligence, automation, compliance, scalability, performance, ease of use, and total cost before selecting a platform.