Powersheet Performance Reference

Modified on Mon, 18 May at 2:37 PM

Customers work with Powersheet on real data — RTM views can span hundreds to thousands of items across multiple hierarchy levels. Performance is not an academic concern: a slow sheet slows down the entire team. That's why we measured performance against representative customer use cases.

Our goal is straightforward: even large sheets should load fast. Concretely, we aim for a "small" sheet — in the range of a few hundred items — to be visible and ready to work with in under 2 seconds.

Benchmark numbers

We benchmark on a 4-level Requirements Traceability Matrix — Customer Requirement → System Requirement → Subsystem Requirement → Design Requirement, each level cross-linked to Test Cases. This represents the traditional V-model process that most ALM customers use in practice.

Project size	Top-level items	Total items in sheet	p95 LCP
Small — component-level RTM	50	~250	1.5 s
Medium — sub-system level RTM	200	~960	2.5 s
Large — full system level RTM	500	~2 400	5 s

Environment: Polarion 2512 with warmed caches, Powersheet 26.4.1, modern business laptop, Microsoft Edge , 100 Mbps connection.
Measured as p95 Largest Contentful Paint — meaning 95 out of 100 opens finish at or below the stated time.

Why LCP? We measure Largest Contentful Paint — the moment the sheet data is visible and readable on screen. This matches what users actually experience: “I can see my requirements traceability matrix and start working.”

Benchmark dataset breakdown

The table below shows the exact number of Work Items in each level of the Requirements Traceability Matrix for each data set size.

Level	Small	Medium	Large
Customer Requirements (L1)	50	200	500
→ Test Cases validating Customer Requirements	21	102	246
System Requirements (L2)	39	136	345
→ Test Cases verifying System Requirements	28	93	255
Subsystem Requirement (L3)	23	112	275
→ Test Cases verifying Subsystem Requirements	32	121	266
Design Requirement (L4)	30	120	300
→ Test Cases verifying Design Requirements	25	114	295
Total unique items	248	961	2401

What affects your numbers

Performance scales with what you put in the sheet. The main factors:

Number of items / rows — the primary driver of load time
Number of columns — more columns mean more data fetched and rendered
Hierarchy depth and link expansion — each additional level in your sheet configuration multiplies the data traversal
Polarion server load — Powersheet depends on Polarion serving the data; a busy or under-resourced server adds time
Cold vs. warm caches — the first open after a server restart is noticeably slower than subsequent opens
Network conditions — VPN, proxy, or slow corporate networks can add visible latency on top of render time

If your sheet loads slower than these numbers, the most common causes are Polarion server load, cold caches, or a sheet configuration with unusually deep expansion paths — see the factors above.

For further diagnosis, contact our technical support team — we'll help you identify the bottleneck specific to your environment. You can also refer to the Troubleshooting performance problems overview for server-side configuration troubleshooting.