We performed a comparison between Palantir Gotham and Qlik Compose based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."This solution is seamless. From one platform, we can do just about anything."
"The technical support is very good. I rate the technical support a ten out of ten."
"I have found it to be a very good, stable, and strong product."
"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."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"It's a stable solution."
"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."
"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."
"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 think there should be less coding involved. Currently, using it involves a tremendous amount of coding."
"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."
"I'd like to have access to more developer training materials."
"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."
"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."
"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."
"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 should be proper documentation available for the implementation process."
Earn 20 points
Palantir Gotham is ranked 33rd in Data Integration with 1 review while Qlik Compose is ranked 20th in Data Integration with 12 reviews. Palantir Gotham is rated 8.0, while Qlik Compose is rated 7.6. The top reviewer of Palantir Gotham writes "A seamless all-in-one solution ". On the other hand, the top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". Palantir Gotham is most compared with Palantir Foundry, Stone Bond Enterprise Enabler, Azure Data Factory and SAS Data Management, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, Azure Data Factory, SSIS and Palantir Foundry.
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