Azure Data Factory vs Informatica Enterprise Data Lake comparison

Microsoft and Informatica are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.1, while Informatica is ranked #39 with an average rating of 7.0. Microsoft holds a 11.0% mindshare in DI, compared to Informatica’s 0.3% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Informatica users who would recommend it.

Azure Data Factory

Read 86 Azure Data Factory reviews

21,615 Views
17,232 Comparison Views

92% willing to recommend

Informatica Enterprise Data...

Read 1 Informatica Enterprise Data Lake review

312 Views
291 Comparison Views

100% willing to recommend

Azure Data Factory

Informatica Enterprise Data...

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and Informatica Enterprise Data Lake based on real PeerSpot user reviews.

Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: December 2024).

Buyer's Guide

Data Integration

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)

Informatica Enterprise Data...

Ranking in Data Integration

39th

Average Rating

7.0

Reviews Sentiment

5.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of December 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.0%, down from 13.3% compared to the previous year. The mindshare of Informatica Enterprise Data Lake is 0.3%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

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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reviewer2330691

Data Architect at a tech services company with 11-50 employees

A scalable tool that needs a lot of maintenance due to its unstable nature

Governance, data dictionary, and data cataloging are not available in Informatica Enterprise Data Lake. A lot of businesses are facing issues related to understanding the area revolving around insights of data. At Informatica Enterprise Data Lake's level, in our company, we have a lot of redundant data in a lot of our core systems. The basic thing that our company wants is for the product to develop a reporting layer and access data from the document layer so that we can avoid duplication in projects, databases, and data. There is a lot of maintenance to be done owing to the instability users may face every time because of the huge processing capacity as the company has around more than 50 nodes, which causes a lot of maintenance issues because of which a lot of people don't benefit from the platform as it functions in a slow manner. Informatica Enterprise Data Lake's setup process was complex since it doesn't support a lot of real-time systems. Every time, we have to find different tools we can use in our company with the solution since it doesn't support many real-time systems. Even if our company invests in some tools, Informatica Enterprise Data Lake creates too many small files with some issues, which we cannot read because we invested in HBase and Kudu, but performance-wise, the process is slow.

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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

"The solution handles large volumes of data very well. One of its best features is its ability to integrate data end-to-end, from pulling data from the source to accessing Databricks. This makes it quite useful for our needs."

"The function of the solution is great."

"The trigger scheduling options are decently robust."

"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."

"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."

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

"An excellent tool for pipeline orchestration."

"The solution can scale very easily."

More Azure Data Factory pros

"The process of using the tool's scalability option is well documented."

Cons

"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."

"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."

"My only problem is the seamless connectivity with various other databases, for example, SAP."

"There are limitations when processing more than one GD file."

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

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

"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."

"I have not found any real shortcomings within the product."

More Azure Data Factory cons

"Informatica Enterprise Data Lake's setup process was complex since it doesn't support a lot of real-time systems."

Pricing and Cost Advice

"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."

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

"This is a cost-effective solution."

"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."

"Data Factory is expensive."

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

More Azure Data Factory pricing and cost advice

"The licenses attached to the solution are highly priced."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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.

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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...

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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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What do you like most about Informatica Enterprise Data Lake?

The process of using the tool's scalability option is well documented.

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What is your experience regarding pricing and costs for Informatica Enterprise Data Lake?

The licenses attached to the solution are highly priced. Informatica has licensing models for every product and for every feature, like the web service feature, which is something my company doesn'...

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What needs improvement with Informatica Enterprise Data Lake?

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Comparisons

Informatica PowerCenter vs Azure Data Factory

Compared 13% of the time

Snowflake vs Azure Data Factory

Compared 10% of the time

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

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

IBM InfoSphere DataStage vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

SSIS vs Informatica Enterprise Data Lake

Compared 100% of the time

More Informatica Enterprise Data Lake Competitors

Product Reports

Buyer's Guide

Azure Data Factory

December 2024

Download Azure Data Factory product report

Buyer's Guide

Data Integration

December 2024

Download Informatica Enterprise Data Lake product report

Also Known As

No data available

Informatica Intelligent Data Lake, Intelligent Data Lake

Learn More

Microsoft

Informatica

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 Intelligent Data Lake enables raw big data to be systematically transformed into fit-for-purpose data sets for a variety of data consumers. Data scientists and analysts can quickly find the data they’re looking for using semantic and faceted search. They can see data profiles, lineage, and other relationships to know whether they can trust the data and whether it’s fit-for-use in their analytic projects.

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

Information Not Available

Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration. Updated: December 2024.

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