We performed a comparison between Azure Data Factory and Qlik Compose based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"An excellent tool for pipeline orchestration."
"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"We haven't had any issues connecting it to other products."
"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."
"It is a scalable solution."
"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."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"It can scale."
"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."
"The technical support is very good. I rate the technical support a ten out of ten."
"There is no built-in pipeline exit activity when encountering an error."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"Data Factory's monitorability could be better."
"Real-time replication is required, and this is not a simple task."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"The speed and performance need to be improved."
"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."
"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."
"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."
"I believe that visual data flow management and the transformation function should be improved."
"There could be more customization options."
"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."
"Qlik's ETL and data transformation could be better."
"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."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Qlik Compose is ranked 20th in Data Integration with 12 reviews. Azure Data Factory is rated 8.0, while Qlik Compose is rated 7.6. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, SSIS, Palantir Foundry and Oracle Data Integrator (ODI). See our Azure Data Factory vs. Qlik Compose report.
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