"The solution is stable and reliable."
"Data catalog and triggers are the two best features for me. AWS Glue has its own data catalog, which makes it great and really easy to use. Triggers are also really good for scheduling the ETL process."
"The key role for Glue is that it hosts our metadata before rolling out our actual data. This is the major advantage of using this solution and our clients client have been very satisfied with it."
"One of the best features of the solution is its ability to easily integrate with other AWS services."
"Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."
"I like that it's flexible, powerful, and allows you to write your own queries and scripts to get the needed transformations."
"AWS Glue's most valuable features are the data catalog, including crawlers and tables, and Glue Studio, which means you don't have to use custom code."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"The BA reporting tools, such as Data Services, and ETL tool in SAP Data Services are the most valuable. When we had in-memory requirements, we used HANA. HANA is most preferably for most the customers for in-memory. SAP is the first company that created the in-memory concept."
"The most valuable feature is the ETL functionality."
"I like how SAP Data Services links reporting and data integration. That's what's most interesting. You also have the opportunity to leverage the power of the Data Services server."
"You can always manipulate a lot of things as long as you have the skill level."
"I appreciate having access to the SAP data."
"The basic functionality is quite good as is the basic logic and data information."
"Data Services' table comparison mechanism is very powerful. It's pretty hard to find a similar feature in other solutions."
"Its integration capabilities and the data migration capabilities are the most valuable. It is very good for SAP and non-SAP tools. It has very good integration with SAP, but it also has the capabilities to connect to other systems. We find it very helpful and stable."
"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."
"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."
"There is a learning curve to this tool."
"There should be more connectors for different databases."
"The monitoring is not that good."
"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."
"Overall, I consider the technical support to be fine, although the response time could be faster in certain cases."
"Source code control is another headache. When your source code base gets too large, managing the source code becomes cumbersome."
"The skillset of data engineers matters a bit to use all the functionality of this solution. Otherwise, the delivery speed won't be faster."
"It would be nice if this solution was a bit easier to move from development to production."
"Data Services SAP is lacking in sources and target databases compared to Informatica. SAP Data Services should have more connectivity."
"It's an ETL that is very good with relational databases but not as good with files and semi-structured files."
"At the integration level, there could be certain set of improvement to connect to various other systems."
"I want some more business intelligence applications. People need to know more and more about data, including the transformation rules, etc. Informatica is a better product for data cataloging. SAP should update the data catalog."
"The migration of the solution between different environments is quite complex."
AWS Glue is ranked 2nd in Cloud Data Integration with 10 reviews while SAP Data Services is ranked 8th in Data Integration Tools with 9 reviews. AWS Glue is rated 8.2, while SAP Data Services is rated 8.0. The top reviewer of AWS Glue writes "Easy to perform ETL on multiple data sources, and easy to use after you learn it". On the other hand, the top reviewer of SAP Data Services writes "It's a powerful tool that does a lot, but it has its annoyances". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, Talend Open Studio, Informatica Cloud Data Integration and SnapLogic, whereas SAP Data Services is most compared with Azure Data Factory, SSIS, Informatica PowerCenter, SAP Process Orchestration and Alteryx Designer.
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.
