AWS Glue vs Pentaho Data Integration and Analytics comparison

Amazon Web Services (AWS) and Hitachi Vantara are both solutions in the Cloud Data Integration category. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 94% of Hitachi Vantara users who would recommend it.

AWS Glue

Read 46 AWS Glue reviews

9,512 Views
6,902 Comparison Views

91% willing to recommend

Pentaho Data Integration an...

Read 52 Pentaho Data Integration and Analytics reviews

2,438 Views
1,080 Comparison Views

94% willing to recommend

AWS Glue

Pentaho Data Integration an...

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Executive Summary

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

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

To learn more, read our detailed AWS Glue vs. Pentaho Data Integration and Analytics Report (Updated: December 2024).

Buyer's Guide

AWS Glue vs. Pentaho Data Integration and Analytics

December 2024

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Categories and Ranking

AWS Glue

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Integration (1st)

Pentaho Data Integration an...

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Integration (24th)

Featured Reviews

Ajaykumar Myana

Senior Software Developer at a computer software company with 10,001+ employees

Provides serverless mechanism, easy data transformation and automated infrastructure management

We no longer had to worry much about infrastructure management because AWS Glue is serverless, and Amazon takes care of the underlying infrastructure. This allowed us to focus on the code and application logic without concerns about scaling, CPU management, or handling fluctuations in flow. The serverless nature of Glue jobs relieved us from these infrastructure-related worries.

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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

"The AWS Glue Data Catalog provides metadata management and schema discovery. AWS Glue simplifies data transformation with automatic schema detection, incremental data updates, and integration with other AWS services."

"The two features I find most valuable in AWS Glue are its user interface and ease of use."

"The solution is stable and reliable."

"Transformations are valuable because you can modify or override complex data logic from an open source or Spark to solve issues."

"The most valuable feature of AWS Glue is its ease of use and good documentation. Additionally, we can do all the transformations that we need."

"I like that it's flexible, powerful, and allows you to write your own queries and scripts to get the needed transformations."

"It's very good to manage."

"The solution’s most valuable feature is the ETL job."

More AWS Glue pros

"The amount of data that it loads and processes is good."

"The area where Lumada has helped us is in the commercial area. There are many extractions to compose reports about our sales team performance and production steps. Since we are using Lumada to gather data from each industry in each country. We can get data from Argentina, Chile, Brazil, and Colombia at the same time. We can then concentrate and consolidate it in only one place, like our data warehouse. This improves our production performance and need for information about the industry, production data, and commercial data."

"It has improved our data integration capabilities."

"The solution has a free to use community version."

"Data transformation within Pentaho is a nice feature that they have and that I value."

"Sometimes, it took a whole team about two weeks to get all the data to prepare and present it. After the optimization of the data, it took about one to two hours to do the whole process. Therefore, it has helped a lot when you talk about money, because it doesn't take a whole team to do it, just one person to do one project at a time and run it when you want to run it. So, it has helped a lot on that side."

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

"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."

More Pentaho Data Integration and Analytics pros

Cons

"I would like to see a more robust interface on the no-code side. This would be nice to be able to split cells."

"Beginners need additional support as it currently lacks some features required for complex transformations, often necessitating custom Python coding."

"The solution could be cheaper. The price of the solution is an area that needs improvement."

"The solution should offer features for streaming data in addition to batching data."

"Setting up pipelines is challenging, especially with version control and testing requirements."

"It fails to handle massive databases acquired from various sources."

"The price of the solution could improve."

"I would like to see stable libraries at the moment they are not there."

More AWS Glue cons

"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."

"One thing that I don't like, just a little, is the backward compatibility."

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

"The reporting definitely needs improvement. There are a lot of general, basic features that it doesn't have. A simple feature you would expect a reporting tool to have is the ability to search the repository for a report. It doesn't even have that capability. That's been a feature that we've been asking for since the beginning and it hasn't been implemented yet."

"In terms of the flexibility to deploy in any environment, such as on-premise or in the cloud, we can do the cloud deployment only through virtual machines. We might also be able to work on different environments through Docker or Kubernetes, but we don't have an Azure app or an AWS app for easy deployment to the cloud. We can only do it through virtual machines, which is a problem, but we can manage it. We also work with Databricks because it works with Spark. We can work with clustered servers, and we can easily do the deployment in the cloud. With a right-click, we can deploy Databricks through the app on AWS or Azure cloud."

"I would like to see improvements made for real-time data processing."

"The web interface is rusty, and the biggest problem with Pentaho is debugging and troubleshooting. It isn't easy to build the pipeline incrementally. At least in our case, it's hard to find a way to execute step by step in the debugging mode."

"I have been facing some difficulties when working with large datasets. It seems that when there is a large amount of data, I experience memory errors."

More Pentaho Data Integration and Analytics cons

Pricing and Cost Advice

"AWS Glue is a paid service that doesn't come under the free trial of AWS."

"AWS Glue uses a pay-as-you-go approach which is helpful. The price of the overall solution is low and is a great advantage."

"AWS Glue follows a pay-as-you-go model, wherein the cost of the data you use will be counted as a monthly bill."

"Its price is good. We pay as we go or based on the usage, which is a good thing for us because it is simple to forecast for the tool. It is good in terms of the financial planning of the company, and it is a good way to estimate the cost. It is also simple for our clients. In my opinion, it is one of the best tools in the market for ETL processes because of the fact that you pay as you use, which separates it from other big tools such as PowerCenter, Pentaho Data Integration, and Talend."

"If you are using the solution for an enterprise business, it will be expensive."

"It is not expensive. AWS Glue works on the serverless architecture. We get charged for the time the server is up. For our use case, we have to use it once in a day, and it is not expensive for us."

"This solution is affordable and there is an option to pay for the solution based on your usage."

"The solution's pricing is based on DPUs so it is a good idea to optimize use or it can get expensive."

More AWS Glue pricing and cost advice

"We did a two or three-year deal the last time we did it. As compared to other solutions, at least so far in our experience, it has been very affordable. The licensing is by component. So, you need to make sure you only license the components that you really intend to use. I am not sure if we have relicensed after the Hitachi acquisition, but previously, multi-year renewals resulted in a good discount. I'm not sure if this is still the case. We've had the full suite for a lot of years, and there is just the initial cost. I am not aware of any additional costs."

"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."

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

"You don't need the Enterprise Edition, you can go with the Community Edition. That way you can use it for free and, for free, it's a pretty good tool to use."

"The solution reduced our ETL development time by a lot because a whole project used to take about a month to get done previously. After having Lumada, it took just a week. For a big company in Brazil, it saves a team at least $10,000 a month."

"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."

"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."

"The pricing has been pretty good. I'm used to using everything open-source or freeware-based. I understand that organizations need to make sure that the solutions are secure, and that's basically where I hit a roadblock in my current organization. They needed to ensure that we had a license and we had a secure way of accessing it so that no outside parties could get access to our data, but in terms of pricing, considering how much other teams are spending on cloud solutions or even their existing solutions, its price point is pretty good. At this time, there are no additional costs. We just have the licensing fees."

More Pentaho Data Integration and Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

22%

Computer Software Company

13%

Manufacturing Company

Insurance Company

Financial Services Firm

23%

Computer Software Company

15%

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 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...

See all answers

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...

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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, ...

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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

AWS Database Migration Service vs AWS Glue

Compared 35% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs AWS Glue

Compared 7% of the time

Informatica PowerCenter vs AWS Glue

Compared 6% of the time

SSIS vs AWS Glue

Compared 5% of the time

Talend Open Studio vs AWS Glue

Compared 4% of the time

More AWS Glue Competitors

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

Compared 15% of the time

SSIS vs Pentaho Data Integration and Analytics

Compared 14% of the time

Talend Open Studio vs Pentaho Data Integration and Analytics

Compared 10% of the time

Azure Data Factory vs Pentaho Data Integration and Analytics

Compared 10% of the time

IBM InfoSphere DataStage vs Pentaho Data Integration and Analytics

Compared 4% of the time

More Pentaho Data Integration and Analytics Competitors

Product Reports

Buyer's Guide

AWS Glue

December 2024

Download AWS Glue product report

Buyer's Guide

Pentaho Data Integration and Analytics

December 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

Amazon Web Services (AWS)

Hitachi Vantara

Overview

AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.

AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates visual creation, running, and monitoring of extract, transform, and load (ETL) pipelines to load data into users' data lakes. This Amazon product seamlessly integrates with other native applications of the brand and allows users to search and query cataloged data using Amazon EMR, Amazon Athena, and Amazon Redshift Spectrum.

The solution also utilizes application programming interface (API) operations to transform users' data, create runtime logs, store job logic, and create notifications for monitoring job runs. The console of AWS Glue connects all of these services into a managed application, facilitating the monitoring and operational processes. The solution also performs provisioning and management of the resources required to run users' workloads in order to minimize manual work time for organizations.

AWS Glue Features

AWS Glue groups its features into four categories - discover, prepare, integrate, and transform. Within those groups are the following features:

Automatic schema discovery: AWS Glue crawlers connect to the organization's source or target data source through a prioritized list of classifiers to determine the schema for users' data. This feature creates metadata in companies' AWS Glue Data Catalog.
Schemas for data stream management: The AWS Glue Schema Registry enables users to validate and control the evolution of streaming data through registered Apache Avro schemas for no additional charge.
Automatic scaling based on workload: This feature dynamically scales resources up and down based on workload. The feature controls job resources, removing them depending on how much the workload can be split up.
FindMatches: This feature is for machine learning-based data deduplication and cleansing, and works by finding records that are imperfect matches of each other to remove useless data copies.
Edit, debug, and test ETL code: This feature helps users who have chosen to interactively develop their ETL code by providing development endpoints for editing, debugging, and testing the code it generates for them.
AWS Glue DataBrew: An interactive, point-and-click visual interface for specialists to clean and normalize data without the need to write any code.
AWS Glue Interactive Sessions: This feature simplifies the development of data integration jobs by enabling data engineers to interactively prepare and explore data.
AWS Glue Studio Job Notebooks: This AWS Glue feature provides serverless notebooks with minimal setup, allowing developers to start working in a timely manner.
Complex ETL pipeline building: This feature allows the product to be invoked on a schedule, on demand, or based on an event, allowing users to start multiple jobs in parallel or specify dependencies to build complex ETL pipelines.
AWS Glue Studio: This AWS Glue feature allows users to visually transform data through a drag-and-drop interface. The product automatically generates the code for ETL processes for users' data.

AWS Glue Benefits

AWS Glue offers a wide range of benefits for its users. These benefits include:

Users of other AWS products can easily onboard with AWS Glue, as it is integrated across a wide range of the company's services.
The solution is serverless, which allows for a lower total cost of ownership.
AWS Glue offers more power for users, as it automates much of the effort in building, maintaining, and running ETL jobs.
The product allows customers to easily discover and search across all their AWS datasets through AWS Glue Data Catalog.
AWS Glue does not require additional payment for managing and enforcing schemas for data streams.
The solution facilitates the authority of scalable ETL jobs for beginners and non-coding experts through a drag-and-drop interface.

Reviews from Real Users

Mustapha A., a cloud data engineer at Jems Groupe, likes AWS Glue because it is a product that is great for serverless data transformations.

Liana I., CEO at Quark Technologies SRL, describes AWS Glue as a highly scalable, reliable, and beneficial pay-as-you-go pricing model.

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

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday

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

Buyer's Guide

AWS Glue vs. Pentaho Data Integration and Analytics

December 2024

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