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Azure Data Factory vs Matillion Data Productivity Cloud comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 6, 2025

Review summaries and opinions

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

ROI

Sentiment score
6.8
Azure Data Factory offers cost-effective, efficient data consolidation for actionable insights, saving time and resources compared to manual processes.
Sentiment score
7.5
Matillion Data Productivity Cloud saves time and reduces costs, offering a rapid ROI and improved efficiencies with integrated platforms.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
Consequently, we adjusted our processes to use Matillion Data Productivity Cloud only for extraction and ingestion, while Snowflake handled all transformations and jobs.
 

Customer Service

Sentiment score
6.4
Azure Data Factory support is generally satisfactory, with responsive assistance, though some users report delays or costly consulting.
Sentiment score
7.6
Matillion Data Productivity Cloud excels in service and support with fast response, comprehensive resources, and high customer satisfaction.
The technical support is responsive and helpful
The technical support from Microsoft is rated an eight out of ten.
The technical support for Azure Data Factory is generally acceptable.
They communicate effectively and respond quickly to all inquiries.
 

Scalability Issues

Sentiment score
7.5
Azure Data Factory is highly scalable and flexible but has room for improvement with third-party integrations and large datasets.
Sentiment score
7.4
Matillion Data Productivity Cloud effectively scales with cloud resources and databases, though managing multiple nodes can be challenging.
Azure Data Factory is highly scalable.
Depending on the nature of data sets, volume, and mixture of different data, the scalability could be improved as manual code writing is still required.
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity.
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is stable and reliable, with occasional issues in responsiveness and large dataset handling.
Sentiment score
7.9
Matillion Data Productivity Cloud is stable and effective, with responsive support; hardware or configurations occasionally cause issues.
The solution has a high level of stability, roughly a nine out of ten.
 

Room For Improvement

Azure Data Factory needs better integration, scheduling, support, AI features, and user interface improvements for efficient data management.
Matillion needs frequent API updates, improved UI, better documentation, more integrations, enhanced scalability, and real-time data capture.
There is a problem with the integration with third-party solutions, particularly with SAP.
The inability to connect local VMs and local servers into the data flow is a limitation that prevents giving Azure Data Factory a perfect score.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
The main areas for improvement are AI features and scalability.
Connections to BigQuery for extracting information are complex.
 

Setup Cost

Azure Data Factory offers competitive, flexible pricing based on usage, with costs integrating Azure services and varying significantly.
Matillion's pricing is competitive, flexible, and cost-effective, with discounts for annual commitments and strategic instance management.
The pricing is cost-effective.
It is considered cost-effective.
Matillion Data Productivity Cloud offers discounts and special deals, especially when dealing with high-volume clients or fewer existing clients in specific regions, like Spain.
The pricing is moderate, neither expensive nor cheap.
 

Valuable Features

Azure Data Factory excels in data integration with user-friendly features, scalability, and over 100 connectors for seamless data movement.
Matillion Data Productivity Cloud enhances ETL processes with user-friendly tools, automation, and security for efficient, scalable data management.
The orchestration features in Azure Data Factory are definitely useful, as it is not only for Azure Data Factory; we can also include DataBricks and other services for integrating the data solution, making it a very beneficial feature.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
It connects to different sources out-of-the-box, making integration much easier.
The predefined connectors eliminate the need to write code for connectivity.
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations.
 

Categories and Ranking

Azure Data Factory
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
92
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (2nd)
Matillion Data Productivity...
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
28
Ranking in other categories
Cloud Data Integration (9th)
 

Mindshare comparison

While both are Data Integration and Access solutions, they serve different purposes. Azure Data Factory is designed for Data Integration and holds a mindshare of 5.6%, down 11.6% compared to last year.
Matillion Data Productivity Cloud, on the other hand, focuses on Cloud Data Integration, holds 5.0% mindshare, up 4.0% since last year.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory5.6%
Informatica PowerCenter6.3%
SSIS5.9%
Other82.2%
Data Integration
Cloud Data Integration Market Share Distribution
ProductMarket Share (%)
Matillion Data Productivity Cloud5.0%
AWS Glue15.3%
AWS Database Migration Service11.9%
Other67.8%
Cloud Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
Jitendra Jena - PeerSpot reviewer
Easy integration and workflow proposals streamline processes
The predefined connectors eliminate the need to write code for connectivity. If you have a predefined connector, it is easy to use with plug and play functionality. The processing time and ease of use are significant benefits. As everyone is moving into AI integration, it will definitely help. When creating workflows, they can propose solutions directly.
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
7%
Financial Services Firm
16%
Computer Software Company
16%
Manufacturing Company
9%
Energy/Utilities Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise55
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise10
Large Enterprise11
 

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 Matillion ETL?
The new version with the Productivity Cloud is very simple. It's easy to use, navigate, and understand.
What is your experience regarding pricing and costs for Matillion ETL?
The pricing is managed by the tooling team. The pricing is moderate, neither expensive nor cheap.
What needs improvement with Matillion ETL?
The main areas for improvement are AI features and scalability.
 

Also Known As

No data available
Matillion ETL for Redshift, Matillion ETL for Snowflake, Matillion ETL for BigQuery
 

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
Thrive Market, MarketBot, PWC, Axtria, Field Nation, GE, Superdry, Quantcast, Lightbox, EDF Energy, Finn Air, IPRO, Twist, Penn National Gaming Inc
Find out what your peers are saying about Azure Data Factory vs. Matillion Data Productivity Cloud and other solutions. Updated: May 2023.
867,370 professionals have used our research since 2012.