Choose a specific buying criteria from the list and see what real users have to say about it.

QlikView Scalability Issues

22ea5d2
BI Expert at a tech services company with 51-200 employees
The product is designed to scale both horizontally and vertically. Some organizatations which have servers and dashboards that handle until 30 Tb of data have had some issues that finally have been addressed by the support service of QlikTech. view full review »
F69f9fbc cbd0 4bbe 917d 18f39a54acf1 avatar?1440164143
Product Manager - Healthcare Analytics at a healthcare company with 51-200 employees
QlikView is a very heavy RAM utilizer (all strong BI tools are). When we hit around 20 concurrent users, the user experience began to suffer. We contacted Qlik Support and they assisted us with a review of our infrastructure. We followed their suggestions to the tee, and were back with great speed! view full review »
Anonymous avatar x60
SAP Application Specialist at a comms service provider with 501-1,000 employees
No issues encountered. view full review »
Anonymous avatar x60
Business Intelligence Director at a tech services company with 51-200 employees
I have not encountered any scalability issues. view full review »
Anonymous avatar x60
Owner at a tech services company with 51-200 employees
In general, the solution is a little problematic in terms of scalability, as everything is stored in RAM. For more complicated analysis for many users, the memory consumption is very high and requires a lot of investment in hardware. view full review »
1cdb933f 5b9d 4cc1 bd53 68a16c6511b7 avatar
Solutions Manager Business Intelligence at a marketing services firm with 51-200 employees
Data model, data size, RAM size, hardware CPUs and UI expressions / charts, are strongly related. It is possible to scale QV without problems, but the issue is more complex than not having enough RAM. Complex expressions at the UI level, single threaded object calculations, complex data models, huge data size, etc., can alter the performance of the QV application and thus we might think we need to scale. There are many tools to measure QV performance and to try keep them at an optimal level. Otherwise, if everything else is fine, we need to increase RAM. Actually, we have 1 TB RAM on our production server. view full review »
Anonymous avatar x60
Consultant at a tech services company
Scalability is directly proportional to RAM size & the number of concurrent users accessing the solutions. We didn't see major stability-related issues post-deployment. view full review »
Anonymous avatar x60
BI Project Leader at a financial services firm with 1,000-5,000 employees
I have encountered issues with scalability. We have generated models with large amounts of data and have found that the processor and memory of our server has been declining. We do not have something to help us to size the equipment requirements when a big data model is developed in QlikView. view full review »
6278fc3f a9ea 477a 863c 26e818a90191 avatar
Head of Qlikview IT at a financial services firm with 1,000-5,000 employees
Scalability depends on the environment and requirements. If you have large data sets, due to the in-memory nature of QlikView, the hardware needs to support your requirements. view full review »
Anonymous avatar x60
Business Analyst at a manufacturing company with 1,000-5,000 employees
Due to in memory technology, when datasets get really huge, rendering of graphs can take some time or even return out of memory. view full review »
Anonymous avatar x60
Associate Consultant at a tech consulting company with 1,000-5,000 employees
We've had no issues with scaling it for our needs. view full review »
0c4b2a8a c131 4969 8596 84974555e75e avatar?1455541186
IT Analyst at a government with 501-1,000 employees
The product eats all memory you give according to the number of accesses it gets, as the navigation is buffered for future queries. Ideally, the datasets must be summarized to the granularity that the public expects. view full review »
B82ef24f 180d 42c4 92d8 2a753caf2757 avatar?1454244289
Analytics Application Consultant Manager at a software R&D company with 51-200 employees
There were no issues with scaling it. view full review »
7ef70fb5 8435 4681 be8f 008952d98549 avatar?1449599161
Senior BI Consultant at a retailer with 51-200 employees
No issues encountered. view full review »
0 7hvkudwfau6ieekkesredu6bhwuimfekerkde2mw60vewavoo4uehoqf8zo?1414330600
Partner at a reseller with 51-200 employees
No view full review »

Sign Up with Email