We performed a comparison between AWS Glue and Denodo 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."AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."
"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."
"The most valuable feature of AWS Glue is that it provides a GUI format with a drag-and-drop feature."
"AWS Glue is fast and managed by AWS. Hence, you don't have to worry about capacity and the performance of Glue jobs. It has integrations with other data stores of AWS. The product offers metadata management, logging, and ETL processing capabilities. It comes with a powerful feature, Glue Studio, which helps to do queries interactively within the community. It is a managed service and very secure. Another popular and mature service is S3."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"The solution's technical support is good. Whenever we raise a use case where we face an issue in our company, we get a response from the solution's technical team."
"Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."
"AWS Glue is a stable and easy-to-use solution."
"Access to numerous forums and internet information."
"The most valuable features of Denodo are the extraction option for adapters, and there are many things for the views, that are cached. Denodo is not storing the data, it looks first to tune the query, and these things are for the agents."
"Denodo's best features are its performance, easy data transformation, and the job scheduler."
"In general, it's good for us to make tests so we can scout the data."
"The most valuable features are data lineage and the concept of a semantic layer."
"Overall, the product works quite well and has a good set of features."
"The data abstraction is the most valuable feature."
"The logical data warehouse functionality is fantastic. It truly stands out. The ClearOptimizer and Virtual Cache are great features. They work together seamlessly to optimize performance."
"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 would like to see a more robust interface on the no-code side. This would be nice to be able to split cells."
"In terms of improvement, the performance of AWS Glue could be faster."
"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."
"I haven't looked into Glue in terms of seeking out flaws. I've not come across missing features."
"There should be more connectors for different databases."
"It would be better if it were more user-friendly. The interesting thing we found is that it was a little strange at the beginning. The way Glue works is not very straightforward. After trying different things, for example, we used just the console to create jobs. Then we realized that things were not working as expected. After researching and learning more, we realized that even though the console creates the script for the ETL processes, you need to modify or write your own script in Spark to do everything you want it to do. For example, we are pulling data from our source database and our application database, which is in Aurora. From there, we are doing the ETL to transform the data and write the results into Redshift. But what was surprising is that it's almost like whatever you want to do, you can do it with Glue because you have the option to put together your own script. Even though there are many functionalities and many connections, you have the opportunity to write your own queries to do whatever transformations you need to do. It's a little deceiving that some options are supposed to work in a certain way when you set them up in the console, but then they are not exactly working the right way or not as expected. It would be better if they provided more examples and more documentation on options."
"The product is expensive for data streaming. This area needs improvement."
"Documentation needs to be improved"
"Sometimes, Windows-related functions do not work properly in Denodo. The analytic functions in SQL do not work properly."
"The feature that you have to connect on LDAP needs improvement."
"The dropdown menus feel antiquated to me, and the administrative portals need improvement."
"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."
"We can't scale it to meet digital requirements."
"Monitoring event logs can be improved. In the older version, there was a monitoring schedule to get event reports and properly audit the reports. In the newer version, it is not there, and we have to manually configure data and audit events."
"User-specific security at the column and row levels needs to be improved. Instead of applying security at every individual level, it would be better if it were at the group or tier level. It will save a lot of time."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Denodo is ranked 8th in Cloud Data Integration with 29 reviews. AWS Glue is rated 7.8, while Denodo is rated 7.8. 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 Denodo writes "Saves our underwriters' time with data virtualization, but could provide more learning resources". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Informatica Enterprise Data Catalog, whereas Denodo is most compared with Azure Data Factory, Delphix, Mule Anypoint Platform, Informatica PowerCenter and Palantir Foundry. See our AWS Glue vs. Denodo report.
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