ER/Studio vs. Fivetran

Data Architect is well suited at organizations of all sizes. It is never too early or unnecessary to enforce proper modelling and design standards on data solutions, and this tool will help that greatly by providing an industry leading data modelling tool, ability to import ETL mappings for data lineage, enforcing and managing naming conventions through the naming convention tool, and publishing of data dictionaries through the report publisher. I was successfully able to build models, provide traceability, and document source to target with lineage throughout for both the business (by providing business definitions in the descriptions), and technical teams (by documenting ETL instructions in text fields) along with field level mapping (by creating "Attachments" representing data sources, tables, and fields) providing easy search capabilities using business friendly terms

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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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• ER/Studio has the ability to provide consistent field names and data types through domains, which are templates. This provides a way to have consistent naming of common fields, like CreatedBy and the data types for the fields. They also have the ability to change all the fields that use that domain to a different data type.
• ER/Studio provides the ability to create custom macros. These macros can be used to apply everything from standard fields based on domains to naming all constraints and indexes. I've also used a macro that comes with ER/Studio to spell check field and table names.
• My favorite feature is the ability to compare your data model to databases for deployments of changes, and to other data models.

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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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• ER\Studio licensing can be cumbersome and upgrading from one version to another usually takes several phone calls and emails to the licensing group to get the update installed and running.
• The repository can be slow when the model count gets larger. By large I mean 20 to 30 models.
• A nice feature that I would like to see is table comments be displayed on the model along with the attributes. Currently you have to choose between the two.

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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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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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I can call or email support and both get quick turn around. The only issue is they are on the west coast (US) and have a west coast work schedule and I'm on the East coast.

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ER/Studio is the most mature, reach in features and quality and therefore useful. Unfortunately, it lacks compatibility with AWS Redshift.

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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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• ER/Studio has had a positive impact on my project as we can develop the data model and have a clear understanding of business needs before we continue with the development phase.

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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