article List of recommended Server Hardware from Qlik Scalability Center in Official Support Articles

List of recommended Server Hardware from Qlik Scalability Center

Sonja_Bauernfeind — Mon, 11 Mar 2024 12:06:09 GMT

General Considerations When Selecting Server Hardware

The purpose of this technical note is to provide starting guidance on what to consider when selecting hardware for the Qlik Associative Engine in Qlik Sense® and QlikView® deployments.

Server selection for any given customer should be based on recommendations and tests provided by trained Qlik professionals. For information on how to contact Qlik's Professional Services, see How and when to contact Qlik's Professional Services and Consulting Teams.

Processor

In current generations (2023) of processors, there is not much difference between AMD and Intel.

Memory

More RAM allows more result sets to be cached, which typically results in better performance.

The Qlik Associative Engine allocates memory uniformly over all available RAM, which means that it is important to always have the amount of memory per CPU socket evenly distributed.

For information on the memory configurations for best performance (including which RAM configurations can be deployed whilst keeping the bus speed as high as possible), contact the server manufacturer.

Architecture

To compare the performance of different servers, you can use the theoretical calculation capacity:

Theoretical Calculation Capacity=#sockets ×#CPU cores×base clock speed

This gives the theoretical number of calculations that a server can do every second. Servers with higher theoretical calculation capacity generally perform better than servers with lower theoretical calculation capacity.

New architectures usually improve on the number of instructions per clock cycle and thus provide improved performance in comparison to older architectures.

Sockets

Since the Qlik Associative Engine is good at using memory as well as the processing capacity of all CPUs, the chipset architecture must provide fast communication between the CPU sockets to keep the latency towards the memory as low as possible. Chipset architectures that allow for direct connections between all available CPU sockets via high bandwidth links are therefore preferred.

Single-socket configurations: Single-socket configurations perform very well as all memory is directly connected to the CPU.
Two-socket configurations: These configurations perform very good providing there is enough bandwidth between the CPUs and towards the memory. For example, Intel CPUs with two or three processor interconnects perform better than those with just one. Using a single Intel CPU in a two-socket configuration also provides good performance.
Four or Eight-socket configurations: In most situations, it is not advised to use these types of configurations with Qlik Sense or QlikView as they more frequently introduce latencies to remote RAM.

Core Count and Clock Speed

It is important to find a good balance between the core count and the clock speed. Even though the Qlik Associative Engine is very good at multi-threading and uses all cores available to it, some procedures are still single-threaded and run faster with higher clock speed.

BIOS and Operating System Settings

Server BIOS and operating system settings can have a significant impact on the performance of Qlik Sense and QlikView deployments. For more information on the recommended settings please visit Quick tips #8 - Server settings for best performance.

The attached recommendations are stored for archival purposes. No additional .pdf's will be created. Server selection for any given customer should be based on recommendations and tests provided by Qlik professional services.

Re: List of recommended Server Hardware from Qlik Scalability Center

kss7374 — Mon, 24 Jan 2022 15:34:38 GMT

Hi Sonja,

Thank you for an interesting and useful review.
Can you tell me if a similar software release is planned by the end of 2021?

Here I looked,

https://www.qlik.com/us/resource-library?searchResources=top+performing+servers#searchResults

tell me where else you can see the current information, the "white list"

Thanks,

BR,

Sergey

Re: List of recommended Server Hardware from Qlik Scalability Center

Sonja_Bauernfeind — Thu, 27 Jan 2022 15:17:50 GMT

Hello @kss7374

The information in the whitepaper is being reviewed, but we do not have an ETA on when a new version will be available.

All the best,
Sonja

Re: List of recommended Server Hardware from Qlik Scalability Center

TobiasW — Wed, 25 Oct 2023 07:48:20 GMT

Hey,

are there newer recommendations then the attached Feb2020 Paper?

Thanks in advance,
Tobi

Re: List of recommended Server Hardware from Qlik Scalability Center

polyakov — Fri, 10 Nov 2023 10:07:58 GMT

Hi!

@Sonja_Bauernfeind Сould you share some new recommendations?

Re: List of recommended Server Hardware from Qlik Scalability Center

Sonja_Bauernfeind — Fri, 10 Nov 2023 10:10:26 GMT

Hello @TobiasW @polyakov

I have reached out internally to see what new information we can share.

Re: List of recommended Server Hardware from Qlik Scalability Center

polyakov — Fri, 10 Nov 2023 10:13:08 GMT

@Sonja_Bauernfeind Thank you very much. This information is very relevant, as potential clients very often ask for clearer recommendations regarding CPU.

Re: List of recommended Server Hardware from Qlik Scalability Center

rva — Mon, 11 Mar 2024 11:09:33 GMT

@Sonja_Bauernfeind : any updates on this topic? Feb 2020 is now more than 4 years ago!

Re: List of recommended Server Hardware from Qlik Scalability Center

Sonja_Bauernfeind — Mon, 11 Mar 2024 12:03:28 GMT

Hello @rva

Please see the updated article. No additional lists of recommended servers will be provided at this point. The previous documents are kept for archiving purposes (I will clarify this better in the article, as I realize this was not done before, thank you for bringing this to my attention).

If you require more direct assistance with sizing and choosing your servers, our professional services are always happy to assist.

All the best,
Sonja