We performed a comparison between Azure Data Factory and SnapLogic 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 trigger scheduling options are decently robust."
"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."
"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."
"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The overall performance is quite good."
"It is easy to deploy workflows and schedule jobs."
"The initial setup is very straightforward."
"An important tool for building prototypes and MVPs than can seamlessly turn into production jobs"
"I found SnapLogic valuable and what I found most valuable about it was its ETL feature. I also found its automation feature valuable. It can be used for automating manual activities. It can be used as a middleware for certain transactional data processing and minimal datasets and ETL activities."
"By using snaps instead of functions in code, you can see the building blocks of the integration visually. This helps a lot."
"The solution is easy to implement and easy to use. It's basically just drag and drop."
"What I found most valuable in SnapLogic is the ETL feature, particularly the Transform Snap Pack, for example, any kind of reading or writing on Transform Snaps. Other than that, all the third-party connectivity tools such as the SAP Snap Pack, Salesforce Snap Pack, Workday Snap Pack, even the ServiceNow Snap Pack, I find all those are pretty useful in SnapLogic."
"SnapLogic is more user-friendly than Boomi in terms of debugging. You can move the mouse to a place, and it will record and show the data easily."
"Despite having no prior experience in SnapLogic, we managed to build, test, and prepare it for release in just three hours, handling heavy data efficiently."
"The initial setup is not very straightforward."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."
"I have not found any real shortcomings within the product."
"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"It needs some more snaps. I would like to see some of the features be changed in some of the snaps."
"What could be improved in SnapLogic is that it was not capable in terms of processing a large number of datasets, but at that point, SnapLogic was evolving. It didn't give a lot of Snaps. I heard recently there are a lot of Snaps getting added and the solution was being enhanced, particularly to connect different data sources. When I was working with SnapLogic six months to one year back, I faced the issue of it not being capable of handling a huge volume of datasets or didn't have much of Snaps, and that was the drawback. If there is any large number of data sets, that's based on or depends on your configuration. If it is a huge volume of data, other traditional ETL tools such as Informatica and Talend can process millions and billions of records, while in SnapLogic, the Snaplex fails or it returns an error in terms of processing that huge volume of data. Informatica, Talend, or any other ETL tool can run for hours in terms of jobs, while SnapLogic jobs fail when the threshold is reached. SnapLogic isn't able to withstand processing, but I don't know if that's still an issue at present, because the solution is getting enhanced and it's been more than six months to one year since I last worked with SnapLogic. There are now a lot of Snaps getting added to the solution, and if it can overcome the limitations I mentioned, SnapLogic could be the go-to tool because currently, it's not being used as much in organizations. It's being used comparatively less compared to other retail tools."
"SnapLogic should have some inbuilt protocol mechanism in order to speed up."
"I would like to see more performance-related dashboards, ones that display the cost of a pipeline, for instance. Also, it would be helpful to have management dashboards for overseeing pipelines and connections."
"There is room for improvement with APM management and how task execution looks."
"The solution isn't ideal for complex processing or logic. We use another solution for that."
"Ultra Pipelines provides real-time ingestion but it needs some adjustment."
"The dashboards regarding scheduled tasks need further improvement."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while SnapLogic is ranked 14th in Data Integration with 21 reviews. Azure Data Factory is rated 8.0, while SnapLogic 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 SnapLogic writes "Easy to set up, easy to use, and is low-code". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas SnapLogic is most compared with IBM InfoSphere DataStage, AWS Glue, Informatica Cloud Data Integration, SSIS and Alteryx Designer. See our Azure Data Factory vs. SnapLogic report.
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