We performed a comparison between Qlik Compose and Qlik Replicate 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."Qlik Compose is good enough. It is user-friendly and intuitive."
"It's a stable solution."
"It is a scalable solution."
"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."
"I have found it to be a very good, stable, and strong product."
"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."
"The technical support is very good. I rate the technical support a ten out of ten."
"It can scale."
"Qlik Replicate stands out with its cutting-edge technology and its ability to handle diverse data management tasks. This powerful tool allows us to efficiently and swiftly load data into various data stores or destinations, while also enabling easy distribution across different endpoints. A notable feature is its capability to reload data from multiple sources by creating multiple tasks within a brief timeframe of fifteen to twenty minutes. This eliminates the need for manual intervention and ensures quick data loading from different tables."
"Support has been great."
"Low-priced reporting and analytics solution, with good scalability and stability. It has on-premises and cloud versions that are cohesive and can integrate well."
"The most useful functions of Qlik Replicate are the data manipulation to transformations."
"We use Qlik Replicate to change data capture of databases in production environments."
"It enables us to transform data at the latest stage rather than in ETL loads, so it's more ELT which is one of the advantages. It is also in near real-time, which brings significant advantage for our embedded analytics approach."
"The CDC and the flexibility to use QVD as a source are the most valuable features of Qlik Replicate."
"From a technical perspective, this is an excellent product."
"There should be proper documentation available for the implementation process."
"I'd like to have access to more developer training materials."
"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."
"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 believe that visual data flow management and the transformation function should be improved."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"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."
"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."
"When you remote into it the Qlik Replicate UI a lot of times it just freezes. We set up the EC2, to allow them to go to the server and click on the Replicate icon, it just opens up and just sits there. At that point, we have to go into the EC2 and then reboot the server. This should be fixed, it is frustrating."
"It's not possible to replicate the QVC files in data analytics."
"In the next release, I would like to see closer integration with data catalyst."
"In various scenarios, an important consideration is when we encounter issues and Qlik Replicate suggests reloading a specific table. If we face any problems or encounter errors with that table, it becomes necessary to make a change in Qlik Replicate. Performing a full reload every time is not feasible or practical. Instead, we should identify the specific issues and address them without repeating the entire reloading process. Based on this approach, we can investigate and resolve the problem by performing targeted loads from the source itself. This change aligns with my perspective and is something I would like to implement."
"The solution's flexibility to work with APIs should also be improved since it is very weak in working with APIs."
"This product could be improved by providing more insight regarding errors. One of our customers that uses Qlik Replicate has had an issue. We tried to debug it, but we could not trace the error message. The infrastructure site should give us more insight about errors. Qlik Replicate is not a business solution, it's an IT solution. The reporting tools and bug site should be improved."
"Support-wise, this solution is in need of improvement."
"Support for this product is not great. It needs to be improved."
Qlik Compose is ranked 20th in Data Integration with 12 reviews while Qlik Replicate is ranked 16th in Data Integration with 13 reviews. Qlik Compose is rated 7.6, while Qlik Replicate is rated 8.2. The top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". On the other hand, the top reviewer of Qlik Replicate writes " Performs well with batch-wise data applications but some features can also be overly dependent on each other". Qlik Compose is most compared with Talend Open Studio, Oracle Data Integrator (ODI), Azure Data Factory, ILANTUS Compact Identity and Palantir Foundry, whereas Qlik Replicate is most compared with Oracle GoldenGate, AWS Database Migration Service, Azure Data Factory, Fivetran and SSIS. See our Qlik Compose vs. Qlik Replicate report.
See our list of best Data Integration vendors.
We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
