We performed a comparison between Matillion ETL and Qlik Compose 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."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."
"Matillion ETL is one hundred percent stable."
"Matillion ETL has great Git integration that is perfect and convenient to use."
"The loading of data is the most valuable feature of Matillion ETL."
"It has helped us to get onto the cloud quickly."
"The most valuable feature of Matillion ETL is its ease of use. If you have had some experience with other solutions, such as Snowflake, the use of this solution will be simple."
"It is pretty user-friendly, even for people who aren't super technical."
"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."
"There were many valuable features, such as extracting any data to put in the cloud. For example, Qlik was able to gather data from SAP and extract SAP data from the platforms."
"I have found it to be a very good, stable, and strong product."
"I like modeling and code generation. It has become a pretty handy tool because of its short ideation to delivery time. From the time you decide you are modeling a data warehouse, and once you finish the modeling, it generates all the code, generates all the tables. All you have to do is tick a few things, and you can produce a fully functional warehouse. I also like that they have added all the features I have asked for over four years."
"It can scale."
"As long as you pick the solution that best fits with your requirements, you won't find that performance is a problem. It's good."
"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."
"The technical support is very good. I rate the technical support a ten out of ten."
"One of the most valuable features of this tool is its automation capabilities, allowing us to design the warehouse in an automated manner. Additionally, we can generate Data Lifecycle Policies (DLP) reports and efficiently implement updates and best practices based on proven design patterns."
"The improvement area could be possible if the tool provides better integration capabilities with other ecosystems, including governance tools or data cataloging tools, as it is currently an area where the solution is lacking."
"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."
"I am looking forward to seeing the expansion of the source range for their data loader product."
"Ideally, I would like it to integrate with Secrets Manager as well as the AWS."
"Our main challenge currently is that Matillion runs on an EC2 instance, limiting us to running only two processes simultaneously at the entry level."
"I found some of the more complex aspects of ETL challenging, but I grasped the concepts fairly quickly."
"The product must enhance its near-real-time data capture feature."
"While the UI is good, it could be improved in its efficiency and made easier to use."
"It could enhance its capabilities in the realm of self-service options as currently, it is more suited for individuals with technical proficiency who can create pages using it."
"My issues with the solution's stability are owing to the fact that it has certain bugs causing issues in some functionalities that should be working."
"When processing data from certain tables with a large volume of data, we encounter significant delays. For instance, when dealing with around one million records, it typically takes three to four hours. To address this, I aim to implement performance improvements across all tables, ensuring swift processing similar to those that are currently complete within seconds. The performance issue primarily arises when we analyze the inserts and updates from the source, subsequently dropping the table. While new insertions are handled promptly, updates are processed slowly, leading to performance issues. Despite consulting our Qlik vendors, they were unable to pinpoint the exact cause of this occurrence. Consequently, I am seeking ways to optimize performance within Qlik Compose, specifically concerning updates."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"For more complex work, we are not using Qlik Compose because it cannot handle very high volumes at the moment. It needs the same batching capabilities that other ETL tools have. We can't batch the data into small chunks when transforming large amounts of data. It tries to do everything in one shot and that's where it fails."
"I'd like to have access to more developer training materials."
"I believe that visual data flow management and the transformation function should be improved."
"The solution has room for improvement in the ETL. They have an ETL, but when it comes to the monitoring portion, Qlik Compose doesn't provide a feature for monitoring."
Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews while Qlik Compose is ranked 20th in Data Integration with 12 reviews. Matillion ETL is rated 8.6, while Qlik Compose is rated 7.6. The top reviewer of Matillion ETL writes "Efficient data integration and transformation with seamless cloud-native integration". On the other hand, the top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". Matillion ETL is most compared with Snowflake, Azure Data Factory, AWS Glue, Informatica PowerCenter and SSIS, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, Azure Data Factory, SSIS and Palantir Foundry. See our Matillion ETL vs. Qlik Compose report.
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