Cisco ThousandEyes vs Zerto
Side-by-side comparison of AI visibility scores, market position, and capabilities
SF internet and cloud network intelligence platform acquired by Cisco. Provides end-to-end visibility into network performance across internet and SaaS paths.
About
Cisco ThousandEyes is a network intelligence platform headquartered in San Francisco that provides enterprises and service providers with end-to-end visibility into digital experience across the internet, cloud infrastructure, and SaaS applications. Originally founded in 2010 and acquired by Cisco in 2020, ThousandEyes operates a distributed network of monitoring agents—deployed in enterprise locations, cloud regions, and backbone provider networks—that continuously measure network path performance, packet loss, latency, and service availability from the perspective of real users. This outside-in monitoring approach gives network and IT teams visibility into segments of the delivery path—including third-party ISPs, CDNs, and cloud providers—that traditional infrastructure monitoring cannot reach.
Zerto delivers continuous data protection and disaster recovery for virtualized and cloud workloads, enabling near-zero RPO recovery as a Hewlett Packard Enterprise product.
About
Zerto is a continuous data protection and disaster recovery platform that uses journal-based replication to capture every write operation to protected virtual machines and cloud workloads, maintaining a rolling recovery journal that enables point-in-time recovery to any second within the journal window rather than only to the most recent backup snapshot. This approach collapses the recovery point objective for protected workloads to near-zero — seconds rather than hours — fundamentally changing the data protection economics for organizations whose business-critical applications cannot tolerate the data loss that snapshot-based backup schedules produce. The platform's continuous replication engine operates at the hypervisor level without agents in protected VMs, capturing changes with minimal performance impact while maintaining the journal that enables granular recovery point selection.
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