What is the difference between Garland Technology EdgeLens vs Mercury?

**Garland Technology EdgeLens**: Bypass TAP/packet broker hybrid for before-and-after inline tool traffic analysis. built by Garland Technology. Core capabilities include Capture network traffic before and after inline security devices (IPS, firewalls, WAFs), Forward traffic copies to out-of-band packet capture, storage, and analysis tools, Historical lookback forensics for post-breach investigation.. **Mercury**: Network metadata capture and analysis tool.. Both serve the Network Detection and Response market but differ in approach, feature depth, and target audience.

Who makes Garland Technology EdgeLens vs Mercury?

**Garland Technology EdgeLens** is developed by Garland Technology. **Mercury** is open-source with 501 GitHub stars. Vendor maturity, funding stage, and team size can be important factors when evaluating long-term viability and support quality.

Is Garland Technology EdgeLens a good alternative to Mercury?

Garland Technology EdgeLens and Mercury serve similar Network Detection and Response use cases: both are Network Detection and Response tools, both cover PCAP, Packet Capture. Key differences: Garland Technology EdgeLens is Commercial while Mercury is Free, Mercury is open-source. Review the feature comparison above to determine which fits your requirements.

Garland Technology EdgeLens vs Mercury: Features, Integrations, Reviews (2026) | CybersecTools

Garland Technology EdgeLens vs Mercury: Side-by-Side Comparison (2026)

Features, pricing, ratings, and pros & cons — compared head-to-head.

Garland Technology EdgeLens is a commercial network detection and response tool by Garland Technology. Mercury is a free network detection and response tool. Compare features, ratings, integrations, and community reviews side by side to find the best network detection and response fit for your security stack.

CST Verdict

Based on our analysis of core features, here is our conclusion:

Mercury

Security teams running flat networks or investigating lateral movement will find Mercury's value in its lightweight metadata capture; the tool costs nothing and requires no agents, making it deployable in minutes across segmented environments where traditional NDR gets blocked by complexity. Its 501 GitHub stars reflect sustained adoption among practitioners who need quick packet context without the overhead of full-packet capture or ML-heavy anomaly scoring. Skip Mercury if your organization needs behavioral baselining or automated response workflows; it's fundamentally a data collection and analysis instrument, not a detection engine.

Data verified Jun 2026

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