We performed a comparison between Denodo and Hitachi Lumada Data Integration based on real PeerSpot user reviews.
Find out in this report how the two Data Integration Tools solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature is Data Catalogs."
"Denodo makes it easy to export data as a service or data link to other services."
"Denodo is lightweight in terms of how it leads you to combine your discrete data systems at one spot."
"Denodo's best features are its performance, easy data transformation, and the job scheduler."
"The most valuable features are query optimization and the single language independence from the sources we're using to catch data."
"In PL/SQL, first you need to gather all the data and then start writing the file, but in Denodo you fetch the data and write the data simultaneously. So, for example, if you have 1 million or 2 million records, you don't have to wait to fetch all of the 2 million; you can keep on fetching and writing in the file simultaneously."
"Data mining is one of the valuable features. We're able to connect all of the data sources with the installed driver, so that is a good advantage in Denodo. Being able to join the tables and view them is also valuable."
"This solution provides us with the ability to sync data, and make it available for anyone to use across the business."
"We use Lumada’s ability to develop and deploy data pipeline templates once and reuse them. This is very important. When the entire pipeline is automated, we do not have any issues in respect to deployment of code or with code working in one environment but not working in another environment. We have saved a lot of time and effort from that perspective because it is easy to build ETL pipelines."
"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."
"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."
"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."
"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's my understanding that the product can scale."
"Flexible deployment, in any environment, is very important to us. That is the key reason why we ended up with these tools. Because we have a very highly secure environment, we must be able to install it in multiple environments on multiple different servers. The fact that we could use the same tool in all our environments, on-prem and in the cloud, was very important to us."
"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."
"There have been some issues when you are at a table. Currently, Denodo exports data sets for a tabular model. When you are finished modeling your database or data warehouse they export a link to be used in Tableau. They should support other tools like Power BI."
"It would be beneficial to make sure that the team that will be using Denodo has some kind of training on how to use the product at least a month beforehand, and there could even be some kind of feedback or Q&A sessions to go along with the training. If Denodo were able to provide this kind of training, it would be very helpful to users in insurance and banking companies because the staff are typically older and not always technically-minded."
"I would like to see a proper way to avoid killing the sourcing systems."
"It would be good if the solution provided a much-needed cellular platform."
"We would like this solution to be more universally user-friendly. At present it is really only aimed at IT specialists."
"Denodo's training documentation could be improved by providing more material. From an administrative standpoint, I've found that only Denodo websites provide the usual tutorials. It may be because it's a bit of a restricted tool, but it results in trouble with learning. Normally, I can find help and solutions from other sources, but I haven't been able to find any for Denodo. Other that, it's fine and it performs well. I only have six months of experience, so I can't accurately suggest improvements."
"Denodo can improve usage management-related aspects. If you deal with the mini views, it gets stuck. The performance is very slow when we go with a large number of views and high volume."
"Tasks such as conversion of a date format or conversion of a number format that can be done in a very easy way in different languages, like SQL or Oracle, are not so easy to do in Denodo. For example, if you want to convert a date from one format to another, in Oracle it's pretty easy; in Denodo, however, it requires so many lines of code. Simple things that can be done very quickly in other database languages require more lines of code in Denodo."
"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."
"In the Community edition, it would be nice to have more modules that allow you to code directly within the application. It could have R or Python completely integrated into it, but this could also be because I'm using an older version."
"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."
"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."
"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."
"Parallel execution could be better in Pentaho. It's very simple but I don't think it works well."
"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."
"Although it is a low-code solution with a graphical interface, often the error messages that you get are of the type that a developer would be happy with. You get a big stack of red text and Java errors displayed on the screen, and less technical people can get intimidated by that. It can be a bit intimidating to get a wall of red error messages displayed. Other graphical tools that are focused at the power user level provide a much more user-friendly experience in dealing with your exceptions and guiding the user into where they've made the mistake."
More Hitachi Lumada Data Integration Pricing and Cost Advice →
Denodo is ranked 10th in Data Integration Tools with 20 reviews while Hitachi Lumada Data Integration is ranked 6th in Data Integration Tools with 24 reviews. Denodo is rated 7.4, while Hitachi Lumada Data Integration is rated 7.8. The top reviewer of Denodo writes "Saves our underwriters' time with data virtualization, but could provide more learning resources". On the other hand, the top reviewer of Hitachi Lumada Data Integration writes "Saves time and makes it easy for our mixed-skilled team to support the product, but more guidance and better error messages are required in the UI". Denodo is most compared with Azure Data Factory, Informatica PowerCenter, Delphix, Informatica Enterprise Data Catalog and SAP HANA, whereas Hitachi Lumada Data Integration is most compared with SSIS, Talend Open Studio, Informatica Enterprise Data Catalog, Azure Data Factory and Spring Cloud Data Flow. See our Denodo vs. Hitachi Lumada Data Integration report.
See our list of best Data Integration Tools vendors.
We monitor all Data Integration Tools 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.
