Azure Data Factory vs SnapLogic comparison

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Azure Data Factory

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Executive SummaryUpdated on Dec 19, 2024

SnapLogic and Azure Data Factory are competing tools in the data integration and management category. SnapLogic has an upper hand in speed and ease of integration, while Azure Data Factory benefits from its extensive features that justify its cost.

Features: SnapLogic offers intuitive data integration with pre-built connectors focusing on rapid deployment, low-code development capabilities, and a user-friendly drag-and-drop interface. Azure Data Factory provides cloud-based data engineering, advanced data orchestration, and seamless integration with other Azure services.

Room for Improvement: SnapLogic could enhance its features for larger enterprise use, provide better support for complex workflows, and improve scalability options. Azure Data Factory might benefit from simplifying its setup process, making cost structures more transparent, and reducing the need for intensive configurations.

Ease of Deployment and Customer Service: SnapLogic's user-friendly design and strong customer support facilitate smooth integrations, offering a straightforward deployment process. In contrast, Azure Data Factory requires more configuration but compensates with detailed documentation and robust Microsoft support.

Pricing and ROI: SnapLogic includes initial setup fees but offers rapid ROI due to its quick deployment and usability. Azure Data Factory may have higher initial costs but promises substantial long-term returns for enterprises invested in the Microsoft ecosystem. Pricing transparency is a noted advantage for SnapLogic, while Azure's cost-effectiveness aligns with its comprehensive features.

To learn more, read our detailed Azure Data Factory vs. SnapLogic Report (Updated: December 2024).

Azure Data Factory vs. SnapLogic

December 2024

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Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

SnapLogic

Ranking in Data Integration

25th

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Process Automation (16th), Cloud Data Integration (14th), Integration Platform as a Service (iPaaS) (10th)

Featured Reviews

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

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.

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Selva Dhoom

Technical Manager at a tech services company with 11-50 employees

Automates manual activities and has helpful documentation that allows users to self-study

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.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Data Factory's most valuable feature is Copy Activity."

"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."

"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."

"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."

"Its integrability with the rest of the activities on Azure is most valuable."

"The scalability of the product is impressive."

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

"Azure Data Factory became more user-friendly when data-flows were introduced."

More Azure Data Factory pros

"SnapLogice is a low-code development tool."

"The product is easy to use and has many connectivity options."

"The feature I found most valuable in SnapLogic is low-code development. Low-code development has been very useful for simple processes, which is required for business users such as extracting details from a file or getting things reported by calling your web service. Calling your web service also becomes easier with SnapLogic because of the snaps available, so if you have the documentation, you can call an API. You don't have to write all those clients to call an API, so that is another feature I found very easy in SnapLogic. Configuring and managing all the file systems also become very handy with the solution."

"The solutions ability to connect "snaps" or components to the graphic user interface is very intuitive, prevents errors, and makes implementations easy."

"By using snaps instead of functions in code, you can see the building blocks of the integration visually. This helps a lot."

"It is a scalable solution."

"The solution could improve its API management."

"You can use other languages, such as Python, and easily connect to other systems."

More SnapLogic pros

Cons

"The user interface could use improvement. It's not a major issue but it's something that can be improved."

"Some of the optimization techniques are not scalable."

"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."

"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."

"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."

"When we initiated the cluster, it took some time to start the process."

"The thing we missed most was data update, but this is now available as of two weeks ago."

"Azure Data Factory uses many resources and has issues with parallel workflows."

More Azure Data Factory cons

"The biggest issue we have faced in our company with SnapLogic is regarding the EDI format"

"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."

"The solution isn't ideal for complex processing or logic. We use another solution for that."

"We'd like zero downtime in the future."

"The problem is that SnapLogic doesn't offer a wide variety of connectors. For example, integrating with Salesforce is not that easy."

"SnapLogic sits somewhere in the middle. It doesn’t offer enough easy canned integrations for its users like some of the easier to use integration apps."

"It needs some more snaps. I would like to see some of the features be changed in some of the snaps."

"The dashboards regarding scheduled tasks need further improvement."

More SnapLogic cons

Pricing and Cost Advice

"It's not particularly expensive."

"This is a cost-effective solution."

"I would not say that this product is overly expensive."

"Pricing is comparable, it's somewhere in the middle."

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

"The pricing model is based on usage and is not cheap."

"I would rate Data Factory's pricing nine out of ten."

"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."

More Azure Data Factory pricing and cost advice

"SnapLogic's price is high compared to the other tools available in the market."

"The pricing is okay."

"By scaling the solution incrementally the cost is controlled and more beneficial to the client."

"I used the free trial."

"The license model is based on consumption."

"When comparing it with solutions like Apigee or MuleSoft, it still offers better value."

"It is a higher initial cost than other easy-to-use integration apps."

"From the ROI perspective, the price is extremely high"

More SnapLogic pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Financial Services Firm

25%

Manufacturing Company

11%

Computer Software Company

Real Estate/Law Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

How do you select the right cloud ETL tool?

AWS Glue and Azure Data factory for ELT best performance cloud services.

How does Azure Data Factory compare with Informatica PowerCenter?

Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...

How does Azure Data Factory compare with Informatica Cloud Data Integration?

Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...

What do you like most about SnapLogic?

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.

What needs improvement with SnapLogic?

The biggest issue we have faced in our company with SnapLogic is regarding the EDI format. For instance, suppose if 20 EDIs are shortlisted then SnapLogic will convert and provide only those specif...

What is your primary use case for SnapLogic?

In our company, we used the solution to build a SnapLogic pipeline in a non-production environment. Presently, our company is releasing it to the production environment. We have used SnapLogic in o...

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Compared 6% of the time

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Compared 5% of the time

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Product Reports

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Azure Data Factory

December 2024

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November 2024

Also Known As

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DataFlow

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Microsoft

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

The SnapLogic Intelligent Integration Platform uses AI-powered workflows to automate all stages of IT integration projects – design, development, deployment, and maintenance – whether on-premises, in the cloud, or in hybrid environments. The platform’s easy-to-use, self-service interface enables both expert and citizen integrators to manage all application integration, data integration, API management, B2B integration, and data engineering projects on a single, scalable platform. With SnapLogic, organizations can connect all of their enterprise systems quickly and easily to automate business processes, accelerate analytics, and drive transformation.

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa

Adobe, ADP, BlackBerry, Bonobos, Box, Capital One, Dannon, Eero, Endo, Gensler, HCL, HP, Grovo, HIS, iRobot, Leica, Merck, Sans, Target, Verizon, Vodafone, Yelp, Yahoo!