We performed a comparison between AWS Glue and Matillion ETL 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."I appreciate AWS Glue for its cost-effectiveness."
"I like the fact that AWS Glue works with Python scripts."
"The solution helps organizations gain flexibility in defining the structure of the data."
"What I like best about AWS Glue is its real-time data backup feature. Last week, there was a production push, and what used to take almost ten days to send out around fifty-six thousand emails now takes only two hours."
"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."
"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."
"AWS Glue's best features are scalability and cloud-based features."
"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 simplicity of this tool is nice. It has a good graphical user interface. You can also do a lot of generic stuff in the tool. If there is good connectivity to a cloud database, such as Snowflake, and you can have a lot of Snowflake functionality in the tool."
"Matillion ETL helps manage data movement, ingestion, and transformation through pipelines."
"The most valuable feature of Matillion ETL is the ETL. The solution is open-source which provides advantages, such as good performance and high efficiency. Additionally, it supports three data types which eliminates predefining the data, and we can write script models in Python."
"It is an incredibly user-friendly and intuitive tool, making the learning curve quite smooth"
"The new version with the Productivity Cloud is very simple. It's easy to use, navigate, and understand."
"The tool's middle-dimensional structure significantly simplifies obtaining the right data at the appropriate level. This feature makes deploying our applications easier since we utilize a single source without publishing data from various sources."
"The product's initial setup phase was easy."
"It can scale to a great extent. It can handle the load that we are putting on it, which is about 5TBs."
"It is not clear how the partition discovery would have been affected by more data coming in."
"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 setup and installation is a bit complex without advanced knowledge or training."
"The crucial problem with AWS Glue is that it only works with AWS. It is not an agnostic tool like Pentaho. In PowerCenter, we can install the forms from Google and other vendors, but in the case of AWS Glue, we can only use AWS."
"The monitoring is not that good."
"AWS Glue would be improved by making it easier to switch from single to multi-cloud."
"The solution's visual ETL tool is of no use for actual implementation."
"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."
"The current version is a bit more limited because it's on a virtual machine, and everything executes on that one virtual machine."
"The product must enhance its near-real-time data capture feature."
"There are certain functions that are available in other ETL tools which are still not present in Matillion ETL. It would be good to have more features."
"When using the SQL loader type there were not a lot of pre-processing features for the data. For example, if there is a table with twenty columns, but we only want to load ten columns. In that case, we can use a security script to select the specific columns needed. However, if we want to perform extensive pre-processing of the data, I faced some challenges with Matillion ETL. I did not encounter many challenges, but my overall experience is limited as I only have three years of experience."
"While the UI is good, it could be improved in its efficiency and made easier to use."
"Matillion’s on-premises capabilities don’t allow you to build something customized."
"The tool's lineage is very weak."
"Performance can be improved for efficiency, and it can be made faster."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews. AWS Glue is rated 7.8, while Matillion ETL is rated 8.6. 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 Matillion ETL writes "Efficient data integration and transformation with seamless cloud-native integration". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Palantir Foundry, whereas Matillion ETL is most compared with Snowflake, Azure Data Factory, Informatica PowerCenter, SSIS and Informatica Cloud Data Integration. See our AWS Glue vs. Matillion ETL report.
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