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AWS Glue vs Pentaho Data Integration and Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

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
6.9
AWS Glue delivers cost-effective efficiency, reducing setup costs and time while providing favorable ROI for limited pipeline needs.
Sentiment score
7.9
Pentaho offers cost-effective integration, reducing ETL time, lowering expenses, and enhancing competitiveness with open-source flexibility and efficiency.
I advocate using Glue in such cases.
 

Customer Service

Sentiment score
6.8
AWS Glue users appreciate technical support for its reliability and helpfulness, but desire improvements in response consistency and fees.
Sentiment score
5.2
Users rely on community support over customer service due to mixed experiences, despite responsive technical support and Hitachi's involvement.
AWS's documentation is reliable, and careful reference often resolves missed upgrade details.
Communication with the vendor is challenging
 

Scalability Issues

Sentiment score
8.0
AWS Glue offers seamless, scalable data handling with serverless architecture, though some see potential for resource management improvements.
Sentiment score
7.3
Pentaho excels in scalability and efficient data handling but faces challenges with exceptionally large data and complex growth scenarios.
It can easily handle data from one terabyte to 100 terabytes or more, scaling nicely with larger datasets.
For jobs requiring multiple RAM usage, we increase the number of workers accordingly.
Pentaho Data Integration handles larger datasets better.
 

Stability Issues

Sentiment score
8.0
AWS Glue is highly reliable, seamlessly integrates with AWS, and benefits from serverless architecture, managed support, and easy troubleshooting.
Sentiment score
7.1
Pentaho Data Integration offers reliability for small to midsize operations but may lag and freeze with complex uses.
AWS Glue is highly stable, and I would rate its stability as nine.
It's pretty stable, however, it struggles when dealing with smaller amounts of data.
 

Room For Improvement

AWS Glue users seek quicker start-up, better UI, Java support, multi-cloud compatibility, cost reduction, and improved documentation and support.
Pentaho needs improvements in big data performance, error handling, UI, scheduling, backward compatibility, cloud integration, and Python support.
A more user-friendly and simpler process would help speed up the deployment process.
With AWS, I gather data from multiple sources, clean it up, normalize it, de-duplicate it, and make it presentable.
Migrating jobs from version 3.0 to 4.0 can present compatibility issues.
Pentaho Data Integration is very friendly, it is not very useful when there isn't a lot of data to handle.
 

Setup Cost

AWS Glue offers flexible pay-as-you-go pricing, affordable yet costly for smaller firms, with extra costs for technical support.
Pentaho offers a cost-effective solution with its free Community Edition and affordable subscription-based Enterprise Edition for varying needs.
The smallest cost for a project is around €700, while the largest can reach up to €7,000 based on the scale of the usage.
AWS charges based on runtime, which can be quite pricey.
Costing depends on resource usage, and cost optimization may involve redesigning jobs for flexibility.
 

Valuable Features

AWS Glue features a user-friendly, scalable interface, ensuring seamless integration, effective ETL tasks, and cost-effective data transformation.
Pentaho provides an intuitive, open-source platform for efficient ETL development and data integration with minimal coding and broad compatibility.
AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models.
For ETL, I feel the performance is excellent. If I create jobs in a standard way, the performance is great, and maintenance is also seamless.
I think if I'm working with big data, common languages like Python work quite nicely, which is advantageous.
It's easy to use and friendly, especially for larger data sets.
 

Categories and Ranking

AWS Glue
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
49
Ranking in other categories
Cloud Data Integration (1st)
Pentaho Data Integration an...
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
53
Ranking in other categories
Data Integration (21st)
 

Featured Reviews

Saurabh Jaiswal - PeerSpot reviewer
Enables seamless integration and data preparation with robust transformation capabilities
AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models. It offers transformation options on canvas or through ETL pipelines, notebooks, and code. Additionally, it supports data preparation, cleaning, and filtering seamlessly. AWS Glue also enhances job scheduling and orchestration capabilities, integrating with AWS Glue Studio for comprehensive data workflow management.
Ryan Ferdon - PeerSpot reviewer
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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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Computer Software Company
13%
Manufacturing Company
8%
Government
6%
Financial Services Firm
22%
Computer Software Company
15%
Government
8%
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 Talend Open Studio compare with AWS Glue?
We reviewed AWS Glue before choosing Talend Open Studio. AWS Glue is the managed ETL (extract, transform, and load) from Amazon Web Services. AWS Glue enables AWS users to create and manage jobs in...
What are the most common use cases for AWS Glue?
AWS Glue's main use case is for allowing users to discover, prepare, move, and integrate data from multiple sources. The product lets you use this data for analytics, application development, or ma...
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...
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, ...
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...
 

Also Known As

No data available
Hitachi Lumada Data Integration, Kettle, Pentaho Data Integration
 

Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
66Controls, Providential Revenue Agency of Ro Negro, NOAA Information Systems, Swiss Real Estate Institute
Find out what your peers are saying about AWS Glue vs. Pentaho Data Integration and Analytics and other solutions. Updated: April 2025.
850,760 professionals have used our research since 2012.