Dell RecoverPoint vs Fivetran comparison

Dell RecoverPoint and Fivetran compete in the data replication and integration solutions category. Dell RecoverPoint has the upper hand in data protection and recovery scenarios, whereas Fivetran shines in ease of integration and data management automation, making it more suitable for data-driven applications.

Features: Dell RecoverPoint excels in block-level replication, seamless integration with VMware's Site Recovery Manager, and efficient bandwidth usage, catering to complex environments with multiple sites. Its continuous and remote data protection capabilities allow for reliable point-in-time recovery. Fivetran offers ease of use in managing data pipelines, automating data syncing with minimal manual intervention, and strong data flow and transformation capabilities. Its extensive connectors and integration capabilities make it highly valuable for diverse data connectivity needs.

Room for Improvement: Dell RecoverPoint could improve its support for broader storage solutions and address high storage consumption by journals. Users suggest enhancements in WAN optimization and VM compatibility. Fivetran faces criticism over high pricing, limited customization, and a need for additional connectors. Users have pointed out the need for better data pipeline observability, improved logging, and enhanced real-time processing speeds.

Ease of Deployment and Customer Service: Dell RecoverPoint is primarily deployed on-premises, offering stability and established support but has varied responsiveness in severe cases. Fivetran supports public and hybrid cloud environments, known for its convenient cloud deployments. While user-friendly, its customer service and pricing processes sometimes face scrutiny.

Pricing and ROI: Dell RecoverPoint offers a one-off licensing model often bundled with EMC storage, considered a good value for data protection despite being pricey. It offers long-term ROI with a perpetual license, especially beneficial for critical data volumes. Fivetran's pricing, seen as expensive, offers a flexible model that scales with data use, making it attractive to larger organizations but less so for smaller setups due to potential costs.