arangodb · Simran-B · Oct 9, 2025 · Oct 10, 2025
diff --git a/site/content/3.12/about-arangodb/features/core.md b/site/content/3.12/about-arangodb/features/core.md
@@ -150,11 +150,9 @@ available from v3.12.5 onward.
   threshold is reached.
 {{% /comment %}}
 
-{{% comment %}} Experimental feature
 - [**Vector search**](../../index-and-search/indexing/working-with-indexes/vector-indexes.md):
   Find items with similar properties by comparing vector embeddings generated by
   machine learning models.
-{{% /comment %}}
 
 - [**Search highlighting**](../../index-and-search/arangosearch/search-highlighting.md):
   Get the substring positions of matched terms, phrases, or _n_-grams.

diff --git a/site/content/3.12/aql/functions/vector.md b/site/content/3.12/aql/functions/vector.md
@@ -16,13 +16,13 @@ You can calculate vector embeddings using [ArangoDB's GraphML](../../data-scienc
 capabilities (available in ArangoGraph) or using external tools.
 
 {{< warning >}}
-The vector index is an experimental feature that you need to enable for the
-ArangoDB server with the `--experimental-vector-index` startup option.
+You need to enable the vector index feature for the
+ArangoDB server with the `--vector-index` startup option.
 Once enabled for a deployment, it cannot be disabled anymore because it
 permanently changes how the data is managed by the RocksDB storage engine
 (it adds an additional column family).
 
-To restore a dump that contains vector indexes, the `--experimental-vector-index`
+To restore a dump that contains vector indexes, the `--vector-index`
 startup option needs to be enabled on the deployment you want to restore to.
 {{< /warning >}}
 

diff --git a/site/content/3.12/index-and-search/indexing/working-with-indexes/vector-indexes.md b/site/content/3.12/index-and-search/indexing/working-with-indexes/vector-indexes.md
@@ -22,17 +22,17 @@ normalized before insertion and search.
 ## How to use vector indexes
 
 {{< warning >}}
-The vector index is an experimental feature that you need to enable for the
-ArangoDB server with the `--experimental-vector-index` startup option.
+You need to enable the vector index feature for the
+ArangoDB server with the `--vector-index` startup option.
 Once enabled for a deployment, it cannot be disabled anymore because it
 permanently changes how the data is managed by the RocksDB storage engine
 (it adds an additional column family).
 
-To restore a dump that contains vector indexes, the `--experimental-vector-index`
+To restore a dump that contains vector indexes, the `--vector-index`
 startup option needs to be enabled on the deployment you want to restore to.
 {{< /warning >}}
 
-1. Enable the experimental vector index feature.
+1. Enable the vector index feature.
 2. Calculate vector embeddings using [ArangoDB's GraphML](../../../data-science/graphml/_index.md)
    capabilities (available in ArangoGraph) or using external tools.
    Store each vector as an attribute in the respective document.
@@ -115,7 +115,6 @@ centroids and the quality of vector search thus degrades.
 {{< tabs "interfaces" >}}
 
 {{< tab "Web interface" >}}
-{{< comment >}}TODO: Only in v3.12.6+
 1. In the **Collections** section, click the name or row of the desired collection.
 2. Go to the **Indexes** tab.
 3. Click **Add index**.
@@ -125,8 +124,6 @@ centroids and the quality of vector search thus degrades.
    under `param`.
 7. Optionally give the index a user-defined name.
 8. Click **Create**.
-{{< /comment >}}
-The web interface does not support vector indexes yet.
 {{< /tab >}}
 
 {{< tab "arangosh" >}}

diff --git a/site/content/3.12/release-notes/version-3.12/api-changes-in-3-12.md b/site/content/3.12/release-notes/version-3.12/api-changes-in-3-12.md
@@ -452,11 +452,11 @@ add the `withHidden=true` query parameter to the call of the endpoint.
 curl "http://localhost:8529/_api/index?collection=myCollection&withHidden=true"
 ```
 
-#### Vector indexes (experimental)
+#### Vector indexes
 
 <small>Introduced in: v3.12.4</small>
 
-A new `vector` index type has been added as an experimental feature.
+A new `vector` index type has been added.
 See [HTTP interface for vector indexes](../../develop/http-api/indexes/vector.md)
 for details.
 

diff --git a/site/content/3.12/release-notes/version-3.12/whats-new-in-3-12.md b/site/content/3.12/release-notes/version-3.12/whats-new-in-3-12.md
@@ -1405,16 +1405,16 @@ Note that it is still forbidden to use `_id` as a top-level attribute or
 sub-attribute in `fields` of persistent indexes. On the other hand, inverted
 indexes have been allowing to index and store the `_id` system attribute.
 
-### Vector indexes (experimental)
+### Vector indexes
 
 <small>Introduced in: v3.12.4</small>
 
-A new `vector` index type has been added as an experimental feature that enables
+A new `vector` index type has been added that enables
 you to find items with similar properties by comparing vector embeddings, which
 are numerical representations generated by machine learning models.
 
-To try out this feature, start an ArangoDB server (`arangod`) with the
-`--experimental-vector-index` startup option. You need to generate
+To use this feature, start an ArangoDB server (`arangod`) with the
+`--vector-index` startup option. You need to generate
 vector embeddings before creating a vector index. For more information about
 the vector index type including the available settings, see the
 [Vector indexes](../../index-and-search/indexing/working-with-indexes/vector-indexes.md)

diff --git a/site/content/3.13/about-arangodb/features/core.md b/site/content/3.13/about-arangodb/features/core.md
@@ -145,11 +145,9 @@ aliases:
   threshold is reached.
 {{% /comment %}}
 
-{{% comment %}} Experimental feature
 - [**Vector search**](../../index-and-search/indexing/working-with-indexes/vector-indexes.md):
   Find items with similar properties by comparing vector embeddings generated by
   machine learning models.
-{{% /comment %}}
 
 - [**Search highlighting**](../../index-and-search/arangosearch/search-highlighting.md):
   Get the substring positions of matched terms, phrases, or _n_-grams.

diff --git a/site/content/3.13/aql/functions/vector.md b/site/content/3.13/aql/functions/vector.md
@@ -16,13 +16,13 @@ You can calculate vector embeddings using [ArangoDB's GraphML](../../data-scienc
 capabilities (available in ArangoGraph) or using external tools.
 
 {{< warning >}}
-The vector index is an experimental feature that you need to enable for the
-ArangoDB server with the `--experimental-vector-index` startup option.
+You need to enable the vector index feature for the
+ArangoDB server with the `--vector-index` startup option.
 Once enabled for a deployment, it cannot be disabled anymore because it
 permanently changes how the data is managed by the RocksDB storage engine
 (it adds an additional column family).
 
-To restore a dump that contains vector indexes, the `--experimental-vector-index`
+To restore a dump that contains vector indexes, the `--vector-index`
 startup option needs to be enabled on the deployment you want to restore to.
 {{< /warning >}}
 

diff --git a/site/content/3.13/index-and-search/indexing/working-with-indexes/vector-indexes.md b/site/content/3.13/index-and-search/indexing/working-with-indexes/vector-indexes.md
@@ -22,17 +22,17 @@ normalized before insertion and search.
 ## How to use vector indexes
 
 {{< warning >}}
-The vector index is an experimental feature that you need to enable for the
-ArangoDB server with the `--experimental-vector-index` startup option.
+You need to enable the vector index feature for the
+ArangoDB server with the `--vector-index` startup option.
 Once enabled for a deployment, it cannot be disabled anymore because it
 permanently changes how the data is managed by the RocksDB storage engine
 (it adds an additional column family).
 
-To restore a dump that contains vector indexes, the `--experimental-vector-index`
+To restore a dump that contains vector indexes, the `--vector-index`
 startup option needs to be enabled on the deployment you want to restore to.
 {{< /warning >}}
 
-1. Enable the experimental vector index feature.
+1. Enable the vector index feature.
 2. Calculate vector embeddings using [ArangoDB's GraphML](../../../data-science/graphml/_index.md)
    capabilities (available in ArangoGraph) or using external tools.
    Store each vector as an attribute in the respective document.

diff --git a/site/content/3.13/release-notes/version-3.12/api-changes-in-3-12.md b/site/content/3.13/release-notes/version-3.12/api-changes-in-3-12.md
@@ -452,11 +452,11 @@ add the `withHidden=true` query parameter to the call of the endpoint.
 curl "http://localhost:8529/_api/index?collection=myCollection&withHidden=true"
 ```
 
-#### Vector indexes (experimental)
+#### Vector indexes
 
 <small>Introduced in: v3.12.4</small>
 
-A new `vector` index type has been added as an experimental feature.
+A new `vector` index type has been added.
 See [HTTP interface for vector indexes](../../develop/http-api/indexes/vector.md)
 for details.
 

diff --git a/site/content/3.13/release-notes/version-3.12/whats-new-in-3-12.md b/site/content/3.13/release-notes/version-3.12/whats-new-in-3-12.md
@@ -1405,16 +1405,16 @@ Note that it is still forbidden to use `_id` as a top-level attribute or
 sub-attribute in `fields` of persistent indexes. On the other hand, inverted
 indexes have been allowing to index and store the `_id` system attribute.
 
-### Vector indexes (experimental)
+### Vector indexes
 
 <small>Introduced in: v3.12.4</small>
 
-A new `vector` index type has been added as an experimental feature that enables
+A new `vector` index type has been added that enables
 you to find items with similar properties by comparing vector embeddings, which
 are numerical representations generated by machine learning models.
 
-To try out this feature, start an ArangoDB server (`arangod`) with the
-`--experimental-vector-index` startup option. You need to generate
+To use this feature, start an ArangoDB server (`arangod`) with the
+`--vector-index` startup option. You need to generate
 vector embeddings before creating a vector index. For more information about
 the vector index type including the available settings, see the
 [Vector indexes](../../index-and-search/indexing/working-with-indexes/vector-indexes.md)