We performed a comparison between Azure Data Factory and Fivetran based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"An excellent tool for pipeline orchestration."
"Its arrays are powerful enough to handle migrations even when the replication is happening in the background, without causing any trouble with the ongoing traffic."
"For us, Fivetran has been able to scale both in terms of the data we bring into our warehouse and the amount of data that we use as well."
"The general data ingestion is valuable. It's used for a lot of data. It provides about 90% of the data we use in our data warehouse without needing data engineering."
"Making the decision to implement Fivetran was supported by the fact that they have better connectors than other competitors."
"The compare feature is the most valuable piece of it."
"The most important feature of the solution is its ability to build data pipelines in less time."
"Fivetran can perform data migration incredibly fast, depending on the source and target."
"The product has some seamless connectors, which are readily available."
"We have experienced some issues with the integration. This is an area that needs improvement."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"The support and the documentation can be improved."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"We require Azure Data Factory to be able to connect to Google Analytics."
"The solution is very expensive. I would like to have a better integration of the solution with Azure."
"Fivetran would be improved by adding the ability to integrate the data from third-party APIs."
"HVR Software's technical support could be improved. Whenever we log a case, the response that we get from the support is a bit delayed."
"The documentation is decent, but it's hard to find information online about Fivetran. For example, if you try to search for an error code, you won't find much information about it in forums."
"Fivetran is very expensive for data sources with a lot of rows, such as email data. I would like to see cheaper pricing for data sources like that."
"The documentation can be laid out better to make it easier to find things, and I really wish there was built-in support for changing passwords. Some features don't work as advertised for the platform/repository database, and HVR is not always the fastest at getting results."
"More connectors are needed for exotic, popular, and rising star portals."
"The environment must be more development-friendly."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Fivetran is ranked 13th in Data Integration with 19 reviews. Azure Data Factory is rated 8.0, while Fivetran is rated 8.0. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of Fivetran writes "Solution reduces time-to-value; high ROI". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Fivetran is most compared with AWS Database Migration Service, Qlik Replicate, Oracle GoldenGate, Informatica Cloud Data Integration and StreamSets. See our Azure Data Factory vs. Fivetran report.
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