We performed a comparison between Qlik Compose and SAS Data Management based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."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."
"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."
"It's a stable solution."
"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."
"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."
"I have found it to be a very good, stable, and strong product."
"I am impressed with the tool's ability to customize."
"The technical support is excellent."
"The product offers very good flexibility."
"In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."
"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."
"This is an established product with powerful data analysis and varied options for user entry points."
"Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools."
"If you compare it to SQL, the memory and development times are very quick."
"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."
"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 is some scope for improvement around the documentation, and a better UI would definitely help."
"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 could be more customization options."
"I believe that visual data flow management and the transformation function should be improved."
"I'd like to have access to more developer training materials."
"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 is quite expensive and hard to install/configure."
"With SAS Data Management, you have to purchase an external driver, configure all of the tables for all of the data that you will extract from Salesforce. It's not a straightforward process."
"The solution could use better documentation."
"The pricing of the solution needs to be improved. They need to work to make it more affordable."
"I would like the tool to include the ability to automate the modifications of the integrations."
"One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools. We can't open those data in other applications. So we need to have that application in place."
"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."
"We find we often have to go back and re-train users when there are changes made to the solution because the changes are not intuitive."
Qlik Compose is ranked 18th in Data Integration with 12 reviews while SAS Data Management is ranked 40th in Data Integration with 15 reviews. Qlik Compose is rated 7.6, while SAS Data Management is rated 8.4. The top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". On the other hand, the top reviewer of SAS Data Management writes "A scalable solution with customer support that is responsive and diligent". Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, Azure Data Factory, SSIS and Palantir Foundry, whereas SAS Data Management is most compared with Informatica PowerCenter, Microsoft Purview, Tungsten RPA, IBM InfoSphere DataStage and Collibra Governance.
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