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."Matillion ETL helps manage data movement, ingestion, and transformation through pipelines."
"It takes less than five minutes to set up and delivers results. It is much quicker than traditional ETL technologies."
"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."
"The product has a good user interface."
"We allow non-technical people to use Matillion to load data into our data warehouse for reporting. Thus, it is easy enough to use that we don't always have to get a technical person involved in setting up a data movement (ETL)."
"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 most valuable feature of Matillion ETL is its user-friendly graphical interface."
"The most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation."
"It's a stable solution."
"It can scale."
"It is a scalable solution."
"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."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"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."
"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."
"Unlike Snowflake which automatically takes care of upgrading to the latest version and includes additional features, with Matillion ETL we need to do this ourselves."
"The product must enhance its near-real-time data capture feature."
"Performance can be improved for efficiency, and it can be made faster."
"To complete the pipeline, they might want to include some connectors which would put the data into different platforms. This would be helpful."
"The cost of the solution is high and could be reduced."
"The current version is a bit more limited because it's on a virtual machine, and everything executes on that one virtual machine."
"Our main challenge currently is that Matillion runs on an EC2 instance, limiting us to running only two processes simultaneously at the entry level."
"It needs integration with more data sources."
"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."
"There should be proper documentation available for the implementation process."
"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."
"It would be better if the first level of technical support were a bit more technically knowledgeable to solve the problem. I think they could also improve the injection of custom scripts. It is pretty difficult to add additional scripts. If the modeling doesn't give you what you want, and you want to change the script generated by the modeling, it is a bit more challenging than in most other products. It is very good with standard form type systems, but if you get a more complicated data paradigm, it tends to struggle with transforming that into a model."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"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."
"There could be more customization options."
Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews while Qlik Compose is ranked 18th 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, SSIS and Informatica PowerCenter, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, Oracle Data Integrator (ODI), Azure Data Factory and ILANTUS Compact Identity. See our Matillion ETL vs. Qlik Compose report.
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