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."It is easy to deploy workflows and schedule jobs."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"In terms of my personal experience, it works fine."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."
"We have been using drivers to connect to various data sets and consume data."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"The product is easy to use and has many connectivity options."
"You can use other languages, such as Python, and easily connect to other systems."
"The API architecture makes it easy for orchestration."
"It is a scalable solution."
"The solutions ability to connect "snaps" or components to the graphic user interface is very intuitive, prevents errors, and makes implementations easy."
"The initial setup is very straightforward."
"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."
"SnapLogic is a great platform for establishing integrations among various systems or patterns by using any kind of interface. If something is not supported by predefined snaps – snaps are connectors in SnapLogic – you can create them (custom snaps) or write a script."
"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."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"The solution needs to be more connectable to its own services."
"There are limitations when processing more than one GD file."
"Data Factory's performance during heavy data processing isn't great."
"Lacks in-built streaming data processing."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"There's space for improvement in the development process of the data pipelines."
"I am looking for more scheduling options. When it comes to scheduling, there are different tools in the market."
"One of the areas for improvement in SnapLogic is that the connectors for some of the applications should be more available in terms of testing in the dev environment. Another area for improvement is that the logging should be standardized, for example, the integration with an ELK stack should be required out-of-the-box, so you can ship the log and have it in the ELK stack. There should be integration with ELK stack for the log shipping."
"Connecting to data behind enterprise firewalls has been tricky."
"The dashboards regarding scheduled tasks need further improvement."
"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."
"Ultra Pipelines provides real-time ingestion but it needs some adjustment."
"We'd like there to be more ways for users to get more comfortable and have more experience with the solution to make it easier to use."
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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We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
