AWS Database Migration Service vs. Fivetran

As stated previously, AWS Database Migration Service excels when replicating very specific data elements between environments. AWS Database Migration Service handles replication tasks to load equipment assets or customer job sites from production to QA databases very well. Full load replication - e.g., we need an exact copy of the production database in another region - works well. But when we need to load the QA database with the latest production data - it does work as well. AWS Database Migration Service comes up short because we do not want to wipe the QA database completely and make an exact copy. We want to keep what's already in the QA database and add production data so that we can QA with that level of volume. And at least with our database design, we end up having to do a lot of manual data manipulation and de-duplication.

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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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• 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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Independently Invited by TrustRadius

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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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Independently Invited by TrustRadius

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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.

Incentivized

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

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.

Incentivized

Independently Invited by TrustRadius

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• Set it and forget it for maintaining data consistency - moderate cost, zero to minimal maintenance
• High touch production data loads into QA - negative ROI engineering time investment far exceeded our predictions

Incentivized

Independently Invited by TrustRadius

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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

Incentivized

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