Azure Data Factory vs Microsoft Analytics Platform System comparison

Azure Data Factory and Microsoft Analytics Platform System are both solutions in the Cloud Data Warehouse category. Additionally, 92% of Azure Data Factory users are willing to recommend the solution, compared to 66% of Microsoft Analytics Platform System users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

14,099 Views
2,538 Comparison Views

92% willing to recommend

Microsoft Analytics Platfor...

Read 9 Microsoft Analytics Platform System reviews

1,688 Views
1,283 Comparison Views

66% willing to recommend

Azure Data Factory

Microsoft Analytics Platfor...

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Executive Summary

We performed a comparison between Azure Data Factory and Microsoft Analytics Platform System based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: August 2026).

Buyer's Guide

Cloud Data Warehouse

August 2026

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Helped 909,725 peers since 2012

Review summaries and opinions

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

Categories and Ranking

Azure Data Factory

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (5th), Cloud Data Warehouse (7th)

Microsoft Analytics Platfor...

Average Rating

6.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Warehouse (18th)

Featured Reviews

Kunal Das

Test Engineer at Happiest Minds Technologies

Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling

If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.

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MahmoudMohamed1

Senior Data Engineer at Tatweer Educational Technologies Company - TETCO

Offers smooth data integration between systems, but requires better real-time analytics capabilities

We leverage its capabilities for many applications. We can integrate with our databases, like Oracle, MySQL, or any other, using Microsoft Integration Services. This lets us continue using private databases without paying additional licensing fees. Additionally, the license includes Analytics services and Power BI, which work on-premises, unlike most other technologies that require cloud solutions.

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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

"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."

"The data is more scalable."

"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."

"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS."

"The initial setup is pretty simple and it can be deployed in a couple of hours."

"The most valuable feature is the ease in which you can create an ETL pipeline."

"The user interface is very good. It makes me feel very comfortable when I am using the tool."

"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."

More Azure Data Factory pros

"I like that it's integrated with other Azure products."

"This solution will connect to any database, you can combine databases, and you can create a cube or tabular model."

"This is a well-integrated solution and that integration empowers results."

"I think Microsoft Stack offers the end-to-end solution I need."

"The most valuable part of the product is that it is a system, with different tools for different services for different kinds of scenarios, making it a very rich, integrated, technology-rich platform whose total integration with the rest of Microsoft products creates flexibility and compatibility and makes the tool a very useful one."

"The result is a highly flexible, affordable, and scalable platform that makes large-scale Hub and Spoke EDW architectures a practical reality."

"We help customers in many ways from customized analysis for detection of anomalies in tax, operations, customer relationship, and marketing campaigns, and we also use mining and ML to help them discover trends, which provides useful information based on their business."

"Microsoft Analytics Platform System's most valuable feature is its ecosystems and seamless integration with other Microsoft reporting platforms and databases."

More Microsoft Analytics Platform System pros

Cons

"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."

"The setup and configuration process could be simplified."

"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."

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

"It would be helpful if they could adjust the data capture feature so that when there are source-side changes ADF could automatically figure it out."

"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."

"Compared to Informatica, it's really crude. I think it's a very crude solution."

"The pricing scheme is very complex and difficult to understand."

More Azure Data Factory cons

"Functionality needs to be more up-to-date with competing products."

"However, centralized EDW tends to be extremely expensive and very inflexible."

"We need better real-time analytics capabilities. It's a bit challenging for us."

"The flexibility of this solution needs to be improved because you cannot make changes at every one of the different steps."

"On a scale from one to ten where one is the worst and ten is the best, I would rate this product overall as a five. This is probably because there is still a lot of room for improvement, features that other products have that are missing, and a lot of open-source technology nowadays that are very good and people can use instead."

"The pricing model needs to be improved."

"The trouble is Microsoft has changed their licensing. It's an extremely expensive product now."

"I think the biggest problem with the product is that it does a data ingest model, which is very expensive."

More Microsoft Analytics Platform System cons

Pricing and Cost Advice

"Data Factory is expensive."

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

"The pricing is a bit on the higher end."

"The licensing cost is included in the Synapse."

"Understanding the pricing model for Data Factory is quite complex."

"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."

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

"Data Factory is affordable."

More Azure Data Factory pricing and cost advice

"The initial price is lower than Oracle, but extensive use of SQL may lead to a higher total cost of ownership."

"We are currently paying $200,000 a year for all the different parts of the suite during an ingest model Microsoft now charges us $700,000 a year."

"Users have to pay extra for premium-level technical support."

"I rate Microsoft Analytics Platform System a seven out of ten for pricing."

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

By reviewers
Company Size	Count
Small Business	4
Large Enterprise	7

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.

See all answers

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...

See all answers

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...

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Comparisons

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Oracle Exadata vs Microsoft Analytics Platform System

Compared 20% of the time

Teradata vs Microsoft Analytics Platform System

Compared 9% of the time

SAP BW4HANA vs Microsoft Analytics Platform System

Compared 6% of the time

SAP IQ vs Microsoft Analytics Platform System

Compared 5% of the time

AWS Lake Formation vs Microsoft Analytics Platform System

Compared 5% of the time

More Microsoft Analytics Platform System Competitors

Product Reports

Buyer's Guide

Azure Data Factory

August 2026

Download Azure Data Factory product report

Buyer's Guide

Microsoft Analytics Platform System

August 2026

Microsoft Analytics Platform System report

Download Microsoft Analytics Platform System product report

Also Known As

No data available

Microsoft APS, MS Analytics Platform System

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.

Microsoft

Microsoft Analytics Platform System integrates with Microsoft ecosystem, connecting databases and offering advanced Cube Solution for analytics. It provides cost-effective end-to-end capabilities with multiple features under one license.

Microsoft Analytics Platform System offers seamless integration with Azure products, and its tools enhance flexibility and compatibility across different services and scenarios. While it provides comprehensive BI charts and data warehousing capabilities, users have noted that support and documentation need improvements, especially in hybrid environments. The system's machine learning and AI could be more user-friendly, and real-time analytics require enhancements. Handling permissions and data ingestion are cost-intensive, posing challenges for non-technical teams.

What are the key features of Microsoft Analytics Platform System?

Seamless Microsoft Ecosystem Integration: Connects efficiently with Microsoft products.
Advanced Cube Solution: Facilitates multidimensional analytics.
Comprehensive End-to-End Capabilities: Covers all analytics needs with one license.
Rich BI Charts: Offers diverse visualization options for insights.
Azure Product Compatibility: Enhances cloud-based analytics and flexibility.

What benefits and ROI can users expect?

Cost-Effective Solution: Multiple features under one license reduce expenses.
Enhanced Productivity: Supports high-level decision-making and operational insights.
Versatility: Suitable for both cloud and on-premise deployments.
Improved Collaboration: Diverse tools aid project execution and teamwork.

In industries such as finance, telecom, and healthcare, Microsoft Analytics Platform System is used for multi-dimensional analysis and business intelligence. It supports predictive analytics, report generation, and server monitoring within Azure settings. Users leverage it for data integration and decision-making, allowing extensive project execution with its suite of tools.

Microsoft

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

Transport for London, E-Plus Mobilfunk GmbH & Co. KG, Prometeia, Tangerine, SSM Health Care, Service Corporation International

Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse. Updated: August 2026.

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