Microsoft Search vs SharePoint Search

An exhaustive, practical guide (with a “when to use what” table for PnP Modern Search Web Parts)

Audience

This article is for people building modern SharePoint portals and search-driven pages, especially using the PnP Modern Search Web Parts (Search Box, Search Results, Filters/Refiners, Vertical, Pagination, etc.).

1) Why this topic is confusing (and why it matters)

In Microsoft 365, “search” is not a single thing. People often mix:

• Search experiences (what users see)
• Search engines/APIs (what actually runs the query)

That confusion leads to classic issues:

• “It works in the SharePoint UI but not in my web part”
• “Adding a deeper folder path returns nothing”
• “Refiners show empty values”
• “Results differ between the suite search bar and the site search page”

If you’re building a PnP Search page, you’re not just “adding a search box”—you’re building a search application. That means picking the right engine and designing metadata intentionally.

2) The two layers: Experience vs Engine

2.1 Search experiences (what the user interacts with)

Microsoft Search is the unified Microsoft 365 search experience that appears across:

• Microsoft 365 header
• SharePoint header
• Office apps (depending on context)
• and sometimes other workload entry points

SharePoint Search is the SharePoint-specific search experience:

• site search pages
• document center patterns
• content-heavy portal search scenarios

2.2 Search engines/APIs (what you integrate with)

When you build custom search (like PnP Modern Search), you usually land on one of these engines:

• SharePoint Search REST API (/_api/search/query)
  Strong SharePoint-centric search features, KQL, refiners, managed properties.
• Microsoft Graph Search API (/search/query)
  Unified cross-M365 search surface, different query model, broader “enterprise search” direction.

Even if both can return SharePoint files, they behave differently and support different customization patterns.

3) What Microsoft Search is (practical definition)

Microsoft Search is designed for enterprise-wide discovery:

• “I don’t know where it is—just find it.”
• It can bring results from multiple workloads (depending on permissions and support).

What Microsoft Search is typically best at:

• Unified discovery across M365 contexts
• Org-level “best answers” such as bookmarks and Q&A style results
• A consistent experience with minimal portal-specific tuning

Where Microsoft Search becomes limiting for portal builders:

• Building classic faceted navigation with stable metadata refiners
• Deep SharePoint-centric tuning via managed properties
• Very precise library/folder scoping patterns used in portal-style UIs

4) What SharePoint Search is (practical definition)

SharePoint Search (as a platform) is designed for SharePoint content applications:

• document portals
• metadata-driven browsing
• controlled search experiences inside a site/portal

Key strengths:

• KQL query language patterns
• Managed properties (and refinable managed properties)
• Refiners with counts and predictable filtering
• Strong control for SharePoint content classification and filtering

For most “PnP Search Web Part portal pages”, SharePoint Search is the more natural foundation.

5) Where PnP Modern Search Web Parts fit

PnP Modern Search Web Parts are a UI layer to build modern search experiences on SharePoint pages.

What PnP Search commonly enables (and why it matters):

• A Search Box connected to Search Results
• A left-side Filters/Refiners panel for metadata-driven exploration
• Custom templates for rendering results as:
  • tables (details list)
  • cards
  • tiles

Because refiners + managed properties are such a core design pattern in PnP Search portals, many real-world implementations gravitate to SharePoint Search REST/KQL behavior as their backbone.

6) The differences that actually impact real solutions

6.1 Query model and precision filtering

SharePoint Search REST is heavily KQL-oriented, and supports patterns that portal builders rely on:

• Path:"..." scoping
• IsDocument:true
• excluding folders (commonly via content type ID patterns)
• filtering via managed properties

Graph Search has a different query model and does not map 1:1 to the classic SharePoint managed property world.

Practical impact:
If your PnP Search solution depends on stable KQL patterns and metadata filtering, SharePoint Search is usually the best fit.

6.2 Refiners (facets) and portal UX

For portal UX, refiners are everything:

• filter by Document Type
• filter by Product
• filter by Category
• filter by Language
• filter by Region
• filter by Status
• etc.

SharePoint Search REST has refiners as a core feature.
Graph Search can support facets in some contexts, but it isn’t a direct replacement for the SharePoint “refinable managed properties” approach.

Practical impact:
PnP Search Filters web part aligns naturally with SharePoint Search refiners.

6.3 Managed properties and search schema control

This is the “make it reliable” foundation.

SharePoint Search lets you:

• map crawled properties → managed properties
• make properties queryable/refinable/sortable
• use RefinableStringXX, RefinableDateXX, etc., for filters

Microsoft Search / Graph is more standardized and less “schema-builder friendly” in the SharePoint sense.

Practical impact:
If your portal is metadata-driven, SharePoint Search schema control is often the deciding factor.

6.4 Cross-workload discovery

This is where Microsoft Search shines.
If your goal is to search:

• SharePoint files
• plus people
• plus Teams messages
• plus Outlook signals

Microsoft Search is the right mental model.

Practical impact:
PnP Search portals are usually about SharePoint content experiences, not “everything everywhere.”

7) Decision table: when to use Microsoft Search vs SharePoint Search (PnP-focused)

Legend: ✅ best fit · ⚠️ possible with tradeoffs · ❌ not recommended

8) Recommended architecture for a PnP Search portal page

8.1 Page composition (baseline)

A clean and scalable setup looks like this:

• PnP Search Box
• PnP Search Filters
• PnP Search Results
• (Optional) Paging, Sorting, Vertical, Export, etc.

8.2 The flow

1. User types a query in Search Box
2. Results web part executes KQL against SharePoint Search REST
3. Filters web part requests refiners for the same query
4. Selecting a filter updates the query and refreshes results

This is how you get a “document portal” experience that feels like a real application.

9) Managed properties strategy (the difference between a demo and a production portal)

9.1 The rule

If you want a filter/refiner, the property must be refinable.

That usually means mapping your SharePoint fields to:

• RefinableStringXX
• RefinableDateXX
• RefinableIntXX
• RefinableDoubleXX

9.2 Why this matters

Without refinable properties:

• filters show empty values
• values don’t appear consistently
• sorting behaves unpredictably
• your portal becomes “search chaos”

9.3 Operational note

After mapping changes:

• reindex the library/site so new schema mappings take effect

10) “Path issues” and how to reduce failures in PnP Search

10.1 The common symptom

“SharePoint UI finds it, but when I add /FolderName/* to Path I get nothing.”

10.2 Why it happens (typical causes)

• The indexed path may not match what you typed (encoding/spaces/canonical URL differences)
• Folder name mismatch (actual folder name vs display name)
• Query becomes too restrictive, and trimming returns nothing
• The content is stored under another URL shape than expected

10.3 Safer baseline query patterns (KQL)

Use these patterns as stable starting points:

Pattern A: Library root scope

Path:"https://contoso.sharepoint.com/sites/Portal/Shared Documents/"
AND IsDocument:true
AND -ContentTypeId:0x0120*

Pattern B: Filter by file type

Path:"https://contoso.sharepoint.com/sites/Portal/Shared Documents/"
AND IsDocument:true
AND (FileExtension:pdf OR FileExtension:docx)
AND -ContentTypeId:0x0120*

Pattern C: Prefer metadata over folders
If folders represent “categories”, consider:

• moving “category” into a metadata column
• mapping it to a refinable managed property
• using refiners instead of deep path constraints

This is the most stable strategy at scale.

11) Practical recommendation (what to choose when using PnP Search)

If your requirement is:

“A modern SharePoint page that behaves like a document search application, with filters and a clean results grid.”

Then the most reliable foundation is:

• SharePoint Search REST + KQL + Managed Properties + Refiners

Microsoft Search remains essential for:

• the global enterprise search bar
• cross-workload discovery
• organization-wide “answers”

Think of it like this:

• Microsoft Search = enterprise discovery
• SharePoint Search = portal/library search applications

Final summary tables

A) Steps to decide

B) Technical comparison