How are you creatively working around the SharePoint List View Threshold

I’ve worked with many different clients medical, manufacturing, food, cosmetics, and now government and the SharePoint List View Threshold is a very common issue everywhere. There are many best practices, but in reality, it’s not always easy to apply them in real‑world environments.

Planning is the most important part: if the site, list, or library structure is designed correctly from the start, SharePoint can handle large datasets without issues.

Here are the technical approaches I use consistently in projects where lists or libraries grow beyond 5K, 20K, or even 100K items.

1) Add indexed columns. With proper indexing, lists and libraries usually perform well up to around 20K items. Index only the columns used in filters, not everything.

2) Plan the structure before creating lists or libraries. Before designing anything, I always ask the business:

• How much data do you generate per year?
• How many documents per department or business unit?
• How long do items stay “active”?

This helps determine whether we need:

• Year‑based partitioning
• Department‑based libraries
• Archive libraries
• Folders or Document Sets
• Power Automate cleanup flows

3) Create libraries based on department, division, business unit, or data type. This keeps each library smaller and easier to manage and aligns with permissions and governance.

4) Use filtered default views such as Active, Open, In Progress, Current Year, Assigned to Me, Department‑wise, or Content/Data Type views. I avoid creating a default view that shows all items without conditions.

Also avoid operations that slow down large lists:

• Using OR filters
• Using “Contains” instead of “Equals”
• Sorting on non‑indexed columns
• Using Group By on large lists

5) Add a Year column to show only the current year’s active data.

6) Use user‑specific views such as Created By = Me or Assigned To = Me.

7) Prefer document libraries over lists. If documents are involved, I don’t recommend using list attachments. Document libraries scale better because:

• They use a different storage engine
• They support folders and document sets
• They handle metadata more efficiently
• They perform better with large item counts

8) Use folders or document sets (1–2 levels max). For scenarios like contracts or user‑specific records, I use:

• A–Z libraries (Library / Folders / Document Sets structure, organized alphabetically)
• Document Sets inside folders
• Folders inside Document Sets
• Document Sets without folders

Note: Folders can also be enabled in lists (disabled by default).

9) Archive old items using Power Automate. I recommend moving old or inactive items to an Archive library. This ensures:

• The active library stays under 5K or 20K items
• Search still finds archived content
• Performance remains stable

Note: If archiving is not feasible and your list or library is already over the threshold and generating errors, another practical option is to create a new list or library for active data or even create year‑wise lists/libraries (2023, 2024, 2025, 2026 etc.). Users may initially find this structure unfamiliar, but it becomes effective when included as part of your training and change‑management process.

10) Use Dataverse when allowed. If Power Apps and Dataverse are permitted:

• Store large, structured datasets in Dataverse
• Store files in SharePoint
• Link them using hyperlinks or lookup fields

Dataverse handles large datasets much better than SharePoint lists. SharePoint works well for documents but not for high‑volume relational data.

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