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Azure Data Factory vs Microsoft Azure Synapse Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Oct 8, 2024
 

Categories and Ranking

Azure Data Factory
Ranking in Cloud Data Warehouse
3rd
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
86
Ranking in other categories
Data Integration (1st)
Microsoft Azure Synapse Ana...
Ranking in Cloud Data Warehouse
2nd
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
90
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 12.9%, down from 13.4% compared to the previous year. The mindshare of Microsoft Azure Synapse Analytics is 9.1%, down from 14.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Q&A Highlights

PS
Aug 03, 2023
 

Featured Reviews

Thulani David Mngadi - PeerSpot reviewer
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.
Sunil Gidwani - PeerSpot reviewer
No competitors provide the entire solution to one place
I rate Azure Synapse Analytics eight out of 10. No competitors provide the entire solution to one place like Synapse. For example, a database just focuses moving and manipulating data, etc. But Synapse is like an all-inclusive workspace. I advise other people to go with Databricks Notebook if you need a computation engine. It has a solid SQL storage procedure. Suppose you are dealing with complex transformation logic and manipulation of run-time data flows. In that case, it's better to use Databricks than any Microsoft ADF. DataBricks looks more promising in terms of computing in memory, so we integrated Databricks in Synapse.

Quotes from Members

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

Pros

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."
"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."
"The data flows were beneficial, allowing us to perform multiple transformations."
"I like that it's a monolithic data platform. This is why we propose these solutions."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The solution has a good interface and the integration with GitHub is very useful."
"Can capture all the transactional data throughout a company."
"The initial setup process is straightforward."
"The most valuable features of Microsoft Azure Synapse Analytics are the user experience because it is easy to make analyses, load different databases, and different resources. Our end users can do the analysis by themselves without IT supervising. This is a great aspect of the solution, it's better for our environment."
"We've had a good experience with technical support in general."
"I love the way all the application resources from Microsoft can synchronize, help me with a lot of stuff, and reduce the time or hour of having maybe a resource for an hour a day while also being able to use artificial intelligence."
"The solution operates like a typical SQL Server environment so there is no alienation in terms of technical knowledge."
"The best thing about it is that it has integration at multiple places. It can talk to more than 90 types of data sources, which is one good thing about it."
"I like the keynotes and their simplicity. Like other Microsoft products, Microsoft Azure Synapse Analytics is simple to understand and use."
 

Cons

"The pricing model should be more transparent and available online."
"The product integration with advanced coding options could cater to users needing more customization."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"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."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"Currently, smaller businesses face a disadvantage in terms of pricing, and reducing costs could address this issue."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"In our company, we always want to improve our data management, including how to manage structured and unstructured data."
"One area for improvement could be better integration with Power BI, as well as data integration with BW."
"Microsoft Azure Synapse Analytics's overall integration within the Azure ecosystem could improve. The native Microsoft solution versus another solution, such as Databricks, there are areas where there could be some improvements."
"We encountered data processing and transformation issues while working with Apache Spark languages for the product."
"The macro functions, though useful, are not totally user-friendly. Some people have difficulties in learning them."
"Integration with other vendors has limitations and could be improved."
"The security performance and cost are the two things that needs improvement."
"We'd, of course, always like to pay less for the service if we can."
 

Pricing and Cost Advice

"The licensing is a pay-as-you-go model, where you pay for what you consume."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"Data Factory is affordable."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"Pricing appears to be reasonable in my opinion."
"ADF is cheaper compared to AWS."
"I understand that Synapse Analytics' pricing is lower than Informatica's."
"Because it's cloud the cost is a different convention and the licensing costs are not the same."
"The price of the package not expensive and depends on how much it is used."
"It's very difficult to price unless you know exactly how the customer is using it."
"The price of Microsoft Azure Synapse Analytics can vary. Other solutions are typically fixed prices and a fixed cost regardless of usage, but this solution is based on usage or consumption."
"Its price could be better. It was a school project, and I got it for free. If I try to pay through my company, it is a little bit more expensive as compared to Oracle."
"Microsoft Azure Synapse Analytics can be costly, however, a cost-effective approach would be to purchase it in advance through reservation for either one or three years. This will significantly reduce the overall expenses incurred."
"Price varies by use-case. You pay for the database itself in addition to any consumed data within Serverless plus other fees if you use the Data Factory that is inside."
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Answers from the Community

PS
Aug 3, 2023
Aug 3, 2023
I know you're looking for someone who's done research for you but realize that's actually something people get paid to do. That said, what you're asking about is a mix of quite different tools when you throw KNIME in the mix. I don't know that tool but sounds like its for specific purpose and it's not an Azure tool. Realize there's endless ETL tools out there. I've used about 1/2 dozen in ...
2 out of 4 answers
reviewer2009835 - PeerSpot reviewer
Apr 27, 2023
A couple of questions before starting the feature comparison:  i. Are you fine with an open-source solution? ii. Any specific reason you have listed ADF? iii. Who will be using these tools and how much learning curve is involved within the team? iv. What kind of data you are dealing with? v. Is data privacy an important factor? vi. Are you looking for only a cloud-based solution or open to a hybrid solution also? vii. What is the maturity level of the team when it comes to working on the cloud ........ These are just a few of the many questions basis which we do self-assessment or measure our preparedness. Let me know if you need more insights. Happy to help!!
BA
Apr 27, 2023
I believe Synapse is not an ETL tool.  ADF is one optional ETL tool for a Synapse Data warehouse.. What Are the Top ETL Tools for Azure Data Warehouse? | Integrate.ioI'd like to step back and pose a bigger option. You see, ETL means making a copy of data you have already. Have you considered a data fabric or mesh, where the data is used where it lies now?  Consider this if your data is already used by some systems, but you need to do a more comprehensive analysis of it.I always want to reduce the replication of databases. The concept of build yet another database to "replace" all the others rarely works out that way.  I'd rather beef up the origination system, or use a replica than build a huge portfolio of ETL programs and an army of ops, data governance, and system support to keep them in sync. Finally, if you really need an ETL tool, i.e. copies of all that data... look for existing talent in your staff. Otherwise, expect to hire some people experienced with the new tool that can advise on design and development and mentor existing staff.
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Educational Organization
44%
Computer Software Company
7%
Financial Services Firm
7%
Manufacturing Company
5%
 

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...
How does Amazon Redshift compare with Microsoft Azure Synapse Analytics?
Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different dat...
What do you like most about Microsoft Azure Synapse Analytics?
The product is easy to use, and anybody can easily migrate to advanced DB.
What is your experience regarding pricing and costs for Microsoft Azure Synapse Analytics?
The cost is reasonable for our company. There is no license cost; we pay only for Azure Compute's costs. It is important to manage the cost efficiently on a daily basis.
 

Also Known As

No data available
Azure Synapse Analytics, Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL DW, Azure SQL Data Warehouse, MS Azure Synapse Analytics
 

Overview

 

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
Toshiba, Carnival, LG Electronics, Jet.com, Adobe, 
Find out what your peers are saying about Azure Data Factory vs. Microsoft Azure Synapse Analytics and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.