Azure Data Factory vs Pentaho Data Integration and Analytics comparison

Microsoft and Hitachi Vantara are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.0, while Hitachi Vantara is ranked #30 with an average rating of 7.8. Microsoft holds a 11.1% mindshare in DI, compared to Hitachi Vantara’s 1.4% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 94% of Hitachi Vantara users who would recommend it.

Azure Data Factory

Read 86 Azure Data Factory reviews

23,087 Views
18,331 Comparison Views

92% willing to recommend

Pentaho Data Integration an...

Read 51 Pentaho Data Integration and Analytics reviews

2,569 Views
1,095 Comparison Views

94% willing to recommend

Azure Data Factory

Pentaho Data Integration an...

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Executive Summary

We performed a comparison between Azure Data Factory and Pentaho Data Integration and Analytics based on real PeerSpot user reviews.

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Azure Data Factory vs. Pentaho Data Integration and Analytics Report (Updated: October 2024).

Buyer's Guide

Azure Data Factory vs. Pentaho Data Integration and Analytics

October 2024

Download the complete report

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Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

Pentaho Data Integration an...

Ranking in Data Integration

30th

Average Rating

8.0

Reviews Sentiment

5.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.1%, down from 13.3% compared to the previous year. The mindshare of Pentaho Data Integration and Analytics is 1.4%, up from 0.5% 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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Ryan Ferdon

Senior Data Engineer at Burgiss

Low-code makes development faster than with Python, but there were caching issues

If you're working with a larger data set, I'm not so sure it would be the best solution. The larger things got the slower it was. It was kind of buggy sometimes. And when we ran the flow, it didn't go from a perceived start to end, node by node. Everything kicked off at once. That meant there were times when it would get ahead of itself and a job would fail. That was not because the job was wrong, but because Pentaho decided to go at everything at once, and something would process before it was supposed to. There were nodes you could add to make sure that, before this node kicks off, all these others have processed, but it was a bit tedious. There were also caching issues, and we had to write code to clear the cache every time we opened the program, because the cache would fill up and it wouldn't run. I don't know how hard that would be for them to fix, or if it was fixed in version 10. Also, the UI is a bit outdated, but I'm more of a fan of function over how something looks. One other thing that would have helped with Pentaho was documentation and support on the internet: how to do things, how to set up. I think there are some sites on how to install it, and Pentaho does have a help repository, but it wasn't always the most useful.

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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 allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."

"The scalability of the product is impressive."

"The data copy template is a valuable feature."

"I like the basic features like the data-based pipelines."

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

"The flexibility that Azure Data Factory offers is great."

"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."

"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."

More Azure Data Factory pros

"The fact that it's a low-code solution is valuable. It's good for more junior people who may not be as experienced with programming."

"The graphical nature of the development interface is most useful because we've got people with quite mixed skills in the team. We've got some very junior, apprentice-level people, and we've got support analysts who don't have an IT background. It allows us to have quite complicated data flows and embed logic in them. Rather than having to troll through lines and lines of code and try and work out what it's doing, you get a visual representation, which makes it quite easy for people with mixed skills to support and maintain the product. That's one side of it."

"One of the valuable features is the ability to use PL/SQL statements inside the data transformations and jobs."

"It is easy to use, install, and start working with."

"Pentaho Data Integration is quite simple to learn, and there is a lot of information available online."

"We also haven't had to create any custom Java code. Almost everywhere it's SQL, so it's done in the pipeline and the configuration. That means you can offload the work to people who, while they are not less experienced, are less technical when it comes to logic."

"I can use Python, which is open-source, and I can run other scripts, including Linux scripts. It's user-friendly for running any object-based language. That's a very important feature because we live in a world of open-source."

"It has improved our data integration capabilities."

More Pentaho Data Integration and Analytics pros

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."

"There is no built-in pipeline exit activity when encountering an error."

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

"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."

"The speed and performance need to be improved."

"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."

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

"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."

More Azure Data Factory cons

"If you're working with a larger data set, I'm not so sure it would be the best solution. The larger things got the slower it was."

"I would like to see more improvements with AS400 DB2."

"Its basic functionality doesn't need a whole lot of change. There could be some improvement in the consistency of the behavior of different transformation steps. The software did start as open-source and a lot of the fundamental, everyday transformation steps that you use when building ETL jobs were developed by different people. It is not a seamless paradigm. A table input step has a different way of thinking than a data merge step."

"Should provide additional control for the data warehouse"

"I would like to see improvement when it comes to integrating structured data with text data or anything that is unstructured. Sometimes we get all kinds of different files that we need to integrate into the warehouse."

"Since Hitachi took over, I don't feel that the documentation is as good within the solution. It used to have very good help built right in."

"I could not connect to our Hadoop environment in an easy and flexible way, and it was important to scale our data warehouse."

"I work with the Community Edition, therefore I do not have support. There was an issue that I could not resolve with community support."

More Pentaho Data Integration and Analytics cons

Pricing and Cost Advice

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

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

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

"It's not particularly expensive."

"The solution's pricing is competitive."

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

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

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

More Azure Data Factory pricing and cost advice

"When we first started with it, it was much cheaper. It has gone up drastically, especially since Hitachi bought out Pentaho."

"I primarily work on the Community Version, which is available to use free of charge."

"The price of the regular version is not reasonable and it should be lower."

"I use it because it is free. I download from their page for free. I don't have to pay for a license. With other tools, I have to pay for the licenses. That is why I use Pentaho."

"I think Lumada's price is fair compared to some of the others, like BusinessObjects, which is was the other thing that I used at my previous job. BusinessObject's price was more reasonable before SAP acquired it. They jacked the price up significantly. Oracle's OBIEE tool was also prohibitively expensive."

"There is a good open source option (Community Edition)."

"We are using the Community Edition. We have been trying to use and sell the Enterprise version, but that hasn't been possible due to the budget required for it."

"The cost of these types of solutions are expensive. So, we really appreciate what we get for our money. Though, we don't think of the solution as a top-of-the-line solution or anything like that."

More Pentaho Data Integration and Analytics 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

23%

Computer Software Company

14%

Government

Comms Service Provider

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.

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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Which ETL tool would you recommend to populate data from OLTP to OLAP?

Hi Rajneesh, yes here is the feature comparison between the community and enterprise edition : https://www.hitachivantara.com/en-us/pdf/brochure/leverage-open-source-benefits-with-assurance-of-hita...

See all answers

What do you think can be improved with Hitachi Lumada Data Integrations?

In my opinion, the reporting side of this tool needs serious improvements. In my previous company, we worked with Hitachi Lumada Data Integration and while it does a good job for what it’s worth, ...

See all answers

What do you use Hitachi Lumada Data Integrations for most frequently?

My company has used this product to transform data from databases, CSV files, and flat files. It really does a good job. We were most satisfied with the results in terms of how many people could us...

See all answers

Comparisons

Informatica PowerCenter vs Azure Data Factory

Compared 14% of the time

Snowflake vs Azure Data Factory

Compared 11% 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

Oracle Data Integrator (ODI) vs Pentaho Data Integration and Analytics

Compared 17% of the time

SSIS vs Pentaho Data Integration and Analytics

Compared 16% of the time

Talend Open Studio vs Pentaho Data Integration and Analytics

Compared 11% of the time

AWS Glue vs Pentaho Data Integration and Analytics

Compared 8% of the time

Informatica PowerCenter vs Pentaho Data Integration and Analytics

Compared 6% of the time

More Pentaho Data Integration and Analytics Competitors

Product Reports

Buyer's Guide

Azure Data Factory

November 2024

Download Azure Data Factory product report

Buyer's Guide

Pentaho Data Integration and Analytics

November 2024

Pentaho Data Integration and Analytics report

Download Pentaho Data Integration and Analytics product report

Also Known As

No data available

Hitachi Lumada Data Integration, Kettle, Pentaho Data Integration

Learn More

Microsoft

Hitachi Vantara

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.

Pentaho Data Integration stands as a versatile platform designed to cater to the data integration and analytics needs of organizations, regardless of their size. This powerful solution is the go-to choice for businesses seeking to seamlessly integrate data from diverse sources, including databases, files, and applications. Pentaho Data Integration facilitates the essential tasks of cleaning and transforming data, ensuring it's primed for meaningful analysis. With a wide array of tools for data mining, machine learning, and statistical analysis, Pentaho Data Integration empowers organizations to glean valuable insights from their data. What sets Pentaho Data Integration apart is its maturity and a vibrant community of users and developers, making it a reliable and cost-effective option. Pentaho Data Integration offers a range of features, including a comprehensive ETL toolkit, data cleaning and transformation capabilities, robust data analysis tools, and seamless deployment options for data integration and analytics solutions, making it a go-to solution for organizations seeking to harness the power of their data.

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

66Controls, Providential Revenue Agency of Ro Negro, NOAA Information Systems, Swiss Real Estate Institute

Buyer's Guide

Azure Data Factory vs. Pentaho Data Integration and Analytics

October 2024

Free Report: Azure Data Factory vs. Pentaho Data Integration and Analytics

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