docs: add Enterprise distributed search reference page (#4625)

Adds the Enterprise reference page at
`docs/web/enterprise/distributed-search.mdx`, following the same
arrangement as Enterprise architecture. The page describes distributed
search and the embedded execution model, with links to shared search
guides. Enterprise architecture links to it, and the official sidebar
lists it immediately after Architecture in the existing Deployment
group.

Adds stable anchors for the RaBitQ and `approx_mode` sections linked by
the Enterprise guide.

Companion: https://github.com/lancedb/sophon/pull/8986 supplies the
detailed Enterprise overlay at the same path. Merge this reference-page
PR first so the overlay has an existing route to replace.

Validation:
- Combined-site assembly with both PR branches passed (309 files).
- Mintlify build validation and link, anchor, and redirect checks
passed.

docs/web/docs.json

@@ -350,6 +350,7 @@
             "pages": [
               "enterprise/index",
               "enterprise/architecture",
+              "enterprise/distributed-search",
               "enterprise/deployment/index",
               "deployment/storage",
               "deployment/monitoring",

docs/web/enterprise/architecture.mdx

@@ -18,3 +18,6 @@ run on machines that can be replaced without any of them owning the data.
 
 [Architecture](/architecture) covers this alongside the embedded form, which is
 the comparison most readers want first.
+
+See [Distributed search](/enterprise/distributed-search) for how Enterprise
+distributes index execution and table-data reads.

docs/web/enterprise/distributed-search.mdx

@@ -0,0 +1,33 @@
+---
+title: "Distributed search"
+sidebarTitle: "Distributed search"
+description: "How LanceDB Enterprise distributes index execution and table-data reads."
+icon: "network-wired"
+availability:
+  oss: unavailable
+  enterprise: available
+  summary: >-
+    LanceDB Enterprise distributes index execution and table-data reads across
+    plan executors. Embedded LanceDB executes searches in the application process.
+---
+
+Distributed search spreads index execution, table-data reads, and caching across
+multiple serving machines in LanceDB Enterprise. Query nodes plan queries and
+combine results. Plan executors cache index structures and table data and execute
+the remote work. See [Enterprise architecture](/enterprise/architecture).
+
+## Embedded search {#embedded-search}
+
+LanceDB OSS runs inside your application process. It searches indexes and reads
+table data using that process's resources, including its index cache. Reading a
+table from object storage does not by itself distribute query execution across
+machines.
+
+## Search interfaces {#search-interfaces}
+
+The shared search guides describe the query APIs and index settings:
+
+- [Vector search](/search/vector-search) and [vector indexes](/indexing/vector-index).
+- [Full-text search](/search/full-text-search) and [FTS indexes](/indexing/fts-index).
+- [Filtering](/search/filtering) and [scalar indexes](/indexing/scalar-index).
+- [Query plans](/search/explain) for inspecting execution and runtime measurements.

docs/web/indexing/vector-index.mdx

@@ -384,7 +384,7 @@ The inner workings of RaBitQ quantization are rather mathematically dense. It ge
 applying a uniformly random, approximately distance-preserving orthogonal transformation of the vertices of the $d$-dimensional hypercube, 
 where $d$ is the dimensionality of the dataset. We defer the details, and an elegant theoretical error bound, to [the original paper.](https://arxiv.org/pdf/2405.12497)
 
-##### Using RaBitQ
+##### Using RaBitQ {#using-rabitq}
 Use RaBitQ quantization by selecting quantized index types ending in the suffix `RQ`. For example, call `create_index` with `index_type="IVF_RQ"`. 
 Note that when using `IVF_RQ`, the dimension of the dataset must be a multiple of `8`.
 

docs/web/search/vector-search.mdx

@@ -235,7 +235,7 @@ The table below summarizes the behavior of `_distance` in search results based o
 See [vector indexes](/indexing/vector-index) for index configuration. The
 following sections cover query-time settings.
 
-### Tuning `approx_mode`
+### Tuning `approx_mode` {#tuning-approx-mode}
 
 Use `approx_mode` when you want to adjust the speed/recall trade-off for approximate vector search at query time. This setting currently applies only to RQ-quantized indexes, such as `IVF_RQ`; other index types ignore it.