We performed a comparison between AWS Glue and MuleSoft Composer 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."
"I like the fact that AWS Glue works with Python scripts."
"I also like that you can add custom libraries like JAR files and use them. So, the ability to use a fast processing engine and embed basic jobs easily are significant advantages."
"Its user interface is quite good. You just need to choose some options to create a job in AWS Glue. The code-generation feature is also useful. If you don't want to customize it and simply want to read a file and store the data in the database, it can generate the code for you."
"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 helps organizations gain flexibility in defining the structure of the data."
"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."
"The advantage of using MuleSoft as part as the Salesforce ecosystem is that anything new they build is guaranteed to work with the new features that are coming from the other side."
"The product is easy to use. You don't need programming skills to use it."
"The prebuilt connectors have saved our customers a lot of time and money."
"The way Composer organizes and manages integration processes is most beneficial. We can easily monitor what's running and what isn't and troubleshoot any data integration issues."
"I have encountered challenges with multi-region support."
"The monitoring is not that good."
"The solution could be cheaper. The price of the solution is an area that needs improvement."
"In terms of performance, if they can further optimize the execution time for serverless jobs, it would be a welcome improvement."
"The solution should offer features for streaming data in addition to batching data."
"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 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."
"We face performance issues when using AWS Glue for data transformation and integration."
"This solution could be improved by offering more integrations with other platforms."
"The technical support team's response time must be improved."
"One additional feature they could add might be something like regional prices. Since we're based in Brazil, we pay in dollars but earn in Brazilian Real."
"MuleSoft Composer needs to improve its interface and scalability."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while MuleSoft Composer is ranked 13th in Cloud Data Integration with 4 reviews. AWS Glue is rated 7.8, while MuleSoft Composer 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 MuleSoft Composer writes "Handles a wide variety of data sources and efficiently organizes and manages integration processes". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, Informatica Cloud Data Integration, SSIS and Talend Open Studio, whereas MuleSoft Composer is most compared with Mule Anypoint Platform, Workato, Celigo Integration Platform, Microsoft Azure Logic Apps and Zapier. See our AWS Glue vs. MuleSoft Composer report.
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