Lacework (now FortiCNAPP) vs Darktrace
Detailed side-by-side comparison to help you choose the right tool
Lacework (now FortiCNAPP)
Data Analysis
AI-powered cloud-native application protection platform providing behavioral threat detection, compliance monitoring, and vulnerability management across multi-cloud environments
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$50,000/yearDarktrace
🟢No CodeBusiness AI Solutions
Self-learning AI cybersecurity platform that creates an Enterprise Immune System, autonomously detecting and responding to sophisticated cyber threats without signatures or rules.
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Starting Price
EnterpriseFeature Comparison
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Lacework (now FortiCNAPP) - Pros & Cons
Pros
- ✓Polygraph behavioral engine automatically baselines normal activity and surfaces anomalies without requiring teams to write and maintain detection rules, dramatically reducing tuning overhead
- ✓Unified CNAPP consolidates CSPM, CWPP, CIEM, Kubernetes security, and vulnerability management into a single platform, replacing multiple point tools and their separate licenses
- ✓Agentless cloud scanning provides rapid time-to-value across AWS, Azure, and GCP accounts, with deeper eBPF agent-based runtime protection available for critical workloads
- ✓Strong attack path analysis correlates vulnerabilities, misconfigurations, and identity risks to prioritize the handful of exposures that actually create exploitable chains
- ✓Post-acquisition integration with the Fortinet Security Fabric enables unified visibility between cloud workload telemetry and network/endpoint security data
- ✓Continuous compliance automation with prebuilt policy packs for PCI DSS, HIPAA, SOC 2, NIST, and CIS saves significant audit preparation effort
Cons
- ✗Enterprise-only pricing with no published tiers or self-serve options makes it inaccessible for smaller teams and creates friction for evaluation
- ✗Brand transition from Lacework to FortiCNAPP has created documentation inconsistencies, confusion about product roadmap, and uncertainty for existing customers during integration
- ✗Initial deployment and onboarding across multi-cloud environments can be complex, particularly when tuning Polygraph baselines for noisy or highly dynamic workloads
- ✗Alert quality improves substantially after several weeks of behavioral learning, meaning early-stage detection can produce false positives before baselines stabilize
- ✗UI and query experience, while improved, still lags behind more recent CNAPP entrants like Wiz in terms of intuitive navigation and graph exploration
Darktrace - Pros & Cons
Pros
- ✓Self-learning AI requires no signatures, rules, or threat-intel feeds — effective on day one against zero-day and novel attacks
- ✓Single platform covers 7 domains (network, email, cloud, OT, identity, endpoint, and AI agents), reducing tool sprawl for SOCs
- ✓Cyber AI Analyst automates Tier-1 triage and reportedly accelerates investigation by 10x, easing analyst burnout
- ✓Autonomous Response (Antigena) takes surgical containment actions at machine speed without disrupting normal business traffic
- ✓Trusted by 10,000+ organizations across 110+ countries, including Fortune 500 firms and critical infrastructure operators
- ✓Named a Leader in the 2025 Gartner Magic Quadrant for Network Detection and Response, validating enterprise-grade maturity
Cons
- ✗Custom enterprise pricing (typically $150K–$500K+/year) puts it out of reach for SMBs and lean security teams
- ✗Requires a 1–4 week behavioral learning period before detection accuracy stabilizes, with elevated false positives early on
- ✗Autonomous response actions need careful tuning to avoid blocking legitimate but unusual business activity
- ✗High alert volume and behavioral context demands experienced SOC analysts to triage effectively
- ✗Deep network sensor deployment and full traffic visibility can be operationally complex in segmented or hybrid environments
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