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."The most valuable feature of AWS Glue is scalability."
"I like the fact that AWS Glue works with Python scripts."
"Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."
"The facility to integrate with S3 and the possibility to use Jupyter Notebook inside the pipeline are the most valuable features."
"AWS Glue's best features are scalability and cloud-based features."
"The solution integrates well with other AWS products or services."
"The solution is stable and reliable."
"The product has a valuable feature for data catalog."
"Provides a good open source option."
"Pentaho Data Integration is quite simple to learn, and there is a lot of information available online."
"I absolutely love Hitachi. I'm one of the forefront supporters of Hitachi for my firm. It's so easy to integrate within our environments. In terms of being able to quickly build ETL jobs, transform, and then automate them, it's really easy to integrate throughout for data analytics."
"The fact that it enables us to leverage metadata to automate data pipeline templates and reuse them is definitely one of the features that we like the best. The metadata injection is helpful because it reduces the need to create and maintain additional ETLs. If we didn't have that feature, we would have lots of duplicated ETLs that we would have to create and maintain. The data pipeline templates have definitely been helpful when looking at productivity and costs."
"It makes it pretty simple to do some fairly complicated things. Both I and some of our other BI developers have made stabs at using, for example, SQL Server Integration Services, and we found them a little bit frustrating compared to Data Integration. So, its ease of use is right up there."
"This solution allows us to create pipelines using a minimal amount of custom coding."
"Lumada has allowed us to interact with our employees more effectively and compensate them properly. One of the cool things is that we use it to generate commissions for our salespeople and bonuses for our warehouse people. It allows us to get information out to them in a timely fashion. We can also see where they're at and how they're doing."
"We're using the PDI and the repository function, and they give us the ability to easily generate reporting and output, and to access data. We also like the ability to schedule."
"The setup and installation is a bit complex without advanced knowledge or training."
"AWS Glue would be improved by making it easier to switch from single to multi-cloud."
"Currently, it supports only two languages in the background: Python and Scala. From our customization point of view, it would be helpful if it can also support Java in the background."
"If there's a cluster-related configuration, we have to make worker notes, which is quite a headache when processing a large amount of data."
"The start-up time is really high right now. For instance, when you start up a new job, you have to wait for five or eight minutes before it starts. If the start-up time is reduced to one or two minutes, it will be great. It will be better to have a direct linkage to Redshift in AWS. If we can use data catalogs from Redshift, it will be so easy to create some data catalogs. Currently, we can only use data catalogs from S3."
"The interface for AWS Glue could improve, they do not put a lot of details. You can write the code, in PySpark or in Scala, which is a big advantage, it is only easy to use for a developer. It will be difficult for new users to enter the cloud environment."
"The solution should offer features for streaming data in addition to batching data."
"One area that could be improved is the ETL view. The drag-and-drop interface is not as user-friendly as some other ETL tools."
"I was not happy with the Pentaho Report Designer because of the way it was set up. There was a zone and, under it, another zone, and under that another one, and under that another one. There were a lot of levels and places inside the report, and it was a little bit complicated. You have to search all these different places using a mouse, clicking everywhere... each report is coded in a binary file... You cannot search with a text search tool..."
"The product needs more plugins."
"It could be better integrated with programming languages, like Python and R. Right now, if I want to run a Python code on one of my ETLs, it is a bit difficult to do. It would be great if we have some modules where we could code directly in a Python language. We don't really have a way to run Python code natively."
"The performance could be improved. If they could have analytics perform well on large volumes, that would be a big deal for our products."
"A big problem after deploying something that we do in Lumada is with Git. You get a binary file to do a code review. So, if you need to do a review, you have to take pictures of the screen to show each step. That is the biggest bug if you are using Git."
"I work with different databases. I would like to work with more connectors to new databases, e.g., DynamoDB and MariaDB, and new cloud solutions, e.g., AWS, Azure, and GCP. If they had these connectors, that would be great. They could improve by building new connectors. If you have native connections to different databases, then you can make instructions more efficient and in a more natural way. You don't have to write any scripts to use that connector."
"Lumada could have more native connectors with other vendors, such as Google BigQuery, Microsoft OneDrive, Jira systems, and Facebook or Instagram. We would like to gather data from modern platforms using Lumada, which is a better approach. As a comparison, if you open Power BI to retrieve data, then you can get data from many vendors with cloud-native connectors, such as Azure, AWS, Google BigQuery, and Athena Redshift. Lumada should have more native connectors to help us and facilitate our job in gathering information from these new modern infrastructures and tools."
"The testing and quality could really improve. Every time that there is a major release, we are very nervous about what is going to get broken. We have had a lot of experience with that, as even the latest one was broken. Some basic things get broken. That doesn't look good for Hitachi at all. If there is one place I would advise them to spend some money and do some effort, it is with the quality. It is not that hard to start putting in some unit tests so basic things don't get broken when they do a new release. That just looks horrible, especially for an organization like Hitachi."
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AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Pentaho Data Integration and Analytics is ranked 22nd in Data Integration with 49 reviews. AWS Glue is rated 7.8, while Pentaho Data Integration and Analytics is rated 8.0. The top reviewer of AWS Glue writes "Provides serverless mechanism, easy data transformation and automated infrastructure management". On the other hand, the top reviewer of Pentaho Data Integration and Analytics writes "It's flexible and can do almost anything I want it to do". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, Informatica Cloud Data Integration, SSIS and Talend Open Studio, whereas Pentaho Data Integration and Analytics is most compared with SSIS, Azure Data Factory, Oracle Data Integrator (ODI), Talend Open Studio and Oracle GoldenGate. See our AWS Glue vs. Pentaho Data Integration and Analytics report.
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We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
