We performed a comparison between Azure Data Factory and Jitterbit Harmony 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."I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"I am one hundred percent happy with the stability."
"The most valuable features are data transformations."
"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."
"We haven't had any issues connecting it to other products."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"Integrity, ease of use, user-friendly user interface, and errorless logs are the most valuable features."
"Easy integration with Salesforce"
"Jitterbit handles the most lines of data in a .csv and loads the quickest of any data loader I have tried."
"The fluid user interface (probably the most user friendly interface, when compared to its competitors)."
"We only use small parts of the solution, however, the parts that we use are quite adequate."
"Jitterbit provides the ability to quickly map data between files and databases."
"It is very easy to build integrations and processes to pull and push data."
"It is a scalable solution."
"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."
"The speed and performance need to be improved."
"The pricing scheme is very complex and difficult to understand."
"The product could provide more ways to import and export data."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."
"The product's technical support has certain shortcomings, making it an area where improvements are required."
"The Microsoft documentation is too complicated."
"Looping through complex data structures can be difficult."
"I know with Salesforce updating the UI like they did, it slowed it down a lot."
"The initial setup can be a little bit difficult."
"In the past few months, there have been some server downtimes during work hours that have affected some critical scheduled integrations."
"You need to have some development skills or hire a Jitterbit engineer to make changes."
"Sometimes we experience disconnections and I have to close all Jitterbit programs."
"Its API management capabilities need improvement."
"There were some bugs in the product. For example if you run a delete query and test, it deletes the actual data."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Jitterbit Harmony is ranked 35th in Data Integration with 13 reviews. Azure Data Factory is rated 8.0, while Jitterbit Harmony is rated 8.6. 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 Jitterbit Harmony writes "An easy-to-setup solution with good stability ". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas Jitterbit Harmony is most compared with Microsoft Azure Logic Apps, Mule Anypoint Platform, MuleSoft Composer, SnapLogic and TIBCO Scribe. See our Azure Data Factory vs. Jitterbit Harmony report.
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