Fivetran vs. Nutanix Cloud Clusters (NC2)

Fivetran's business model justifies the use-case where we require data from a single source basically a lot of data but if the requirement is not on the heavier side, Fivetran comes to costly operation when compared to its peers. Otherwise, I'll recommend Fivetran for stability and update and seamless service provider.

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Most suitable as a stepping stone from traditional on premise or private cloud offerings into native public cloud, or to supplement native public cloud workloads. Less suitable for hosting modern architected workloads as there is reduced ability to scale.

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• Easily connects to source data using delivered connectors
• Transforms data into standard models and schemas
• Has very good documentation to help quickly setup connectors

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• Very difficult to get connectors enhanced if a specific needed object is not supported by them
• Depending on the edition needed and the data volumes, can get quite expensive

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Very easy and intuitive to setup and maintain as there usually are not that many options. Very well documented (e.g. how to setup each connector, how the schema looks like, any specific features of this connector etc.). Also the operation is intuitive, e.g. you have status pages, log pages, configuration pages etc. for each connector.

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Overall, relatively easy to use - although will certainly feel different to some other popular Hypervisors.

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It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.

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We never seriously considered using anything else. Our data engineers had used Fivetran extensively in previous roles so when it came time to make a decision, there wasn't much of a process. They gladly signed the contract with Fivetran pretty quickly.

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As a direct replacement of VMWare on AWS, Nutanix Cloud Clusters (NC2) offers reduced costs, improved contract conditions, the ability to directly consume AWS resources, and to apply AWS Savings Plans.

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• It has been very positive in serving BI team with new source requests
• It has been OK at scaling to match as data volumes as source data size grows

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info