[Django] #36517: Add Native Vector Support for Oracle: VectorField, VectorIndex, and VectorDistance

[Django]

#36517: Add Native Vector Support for Oracle: VectorField, VectorIndex, and
VectorDistance
-------------------------------------+-------------------------------------
Reporter: SAVAN SONI | Type: New
| feature
Status: new | Component: Database
| layer (models, ORM)
Version: dev | Severity: Normal
Keywords: | Triage Stage:
| Unreviewed
Has patch: 0 | Needs documentation: 0
Needs tests: 0 | Patch needs improvement: 0
Easy pickings: 0 | UI/UX: 0
-------------------------------------+-------------------------------------
This feature adds native support for Oracle’s Vector:
[https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse
/overview-ai-vector-search.html] data type introduced in Oracle 23c. It
enables AI and ML applications to store and query high-dimensional data
directly in the database using a new VectorField model field, VectorIndex
support for similarity search, and ORM expressions for vector operations.



== Features Included:

**VectorField model field:

1. Accepts optional dimensions, storage_format, and storage_type
arguments.

2. Supports Dense and Sparse vector storage.

3. Auto-converts lists, NumPy arrays, and oracledb.SparseVector for
insert/update.


**Vector Index support:

1. VectorIndex class using Meta.indexes.

2. Support for HNSW and IVF index types.

3. Optional parameters: distance, accuracy, parallel, etc.

**Vector distance expressions and lookups:

1. Custom Func class VectorDistance for VECTOR_DISTANCE(lhs, rhs, metric)

2. CosineDistance, EuclideanDistance, and NegativeDotProduct etc. as
lookups.

3. Query syntax via filter() and order_by() for similarity search.


== Testing:

1. Dense and Sparse vector insert/query tests added.

2. Stress test scripts for repeated inserts/queries included.

== Example:

{{{
from django.db import models
VectorIndex = model.VectorIndex
VectorDistanceType = models.VectorDistanceType
VectorIndexType = models.VectorIndexType

class Product(models.Model):
name = models.CharField(max_length=100)
embedding = models.VectorField(dim=3,
storage_format=VectorStorageFormat.FLOAT32,
storage_type=VectorStorageType.DENSE)

class Meta:
indexes = [
VectorIndex(
fields=["embedding"],
name="vec_idx_product",
index_type=VectorIndexType.HNSW,
distance=VectorDistanceType.COSINE,
)
]

}}}

And a Similarity search can be performed

{{{
query_vector = array.array("f", [1.0, 2.0, 3.0])

products = Product.objects.annotate(
score=VectorDistance(
"embedding",
query_vector,
metric=VectorDistanceType.COSINE,
)
).order_by("score")[:5]
}}}


== Implementation Status
We have already implemented:

1. Custom VectorField with support for DENSE and SPARSE formats

2. Automatic SQL generation for model/table creation

3. VectorIndex support with customizable parameters and distance metrics

4. ORM expressions and lookups for vector distance queries (e.g.,
CosineDistance, EuclideanDistance)

5. Basic tests for dense vector creation, insertion, indexing, and
querying

6. Integration with Oracle’s Python driver (oracledb) for runtime behavior

== PR Readiness

We have finalized the major components of this feature and are ready to
open a public pull request after community feedback or approval of this
feature proposal.
--
Ticket URL: <https://code.djangoproject.com/ticket/36517>
Django <https://code.djangoproject.com/>
The Web framework for perfectionists with deadlines.

[Django]

#36517: Add Native Vector Support for Oracle: VectorField, VectorIndex, and
VectorDistance
-------------------------------------+-------------------------------------

Reporter: SAVAN SONI | Owner: (none)

Type: New feature | Status: new

Component: Database layer | Version: dev
(models, ORM) |
Severity: Normal | Resolution:

Keywords: | Triage Stage:
| Unreviewed
Has patch: 0 | Needs documentation: 0
Needs tests: 0 | Patch needs improvement: 0
Easy pickings: 0 | UI/UX: 0
-------------------------------------+-------------------------------------

Description changed by SAVAN SONI:

Old description:

New description:

This feature adds native support for the Oracle Database’s
[https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse
/overview-ai-vector-search.html Vector data type] introduced in Oracle

--
Ticket URL: <https://code.djangoproject.com/ticket/36517#comment:1>

[Django]

#36517: Add Native Vector Support for Oracle: VectorField, VectorIndex, and
VectorDistance
-------------------------------------+-------------------------------------
Reporter: SAVAN SONI | Owner: (none)

Type: New feature | Status: closed

Component: Database layer | Version: dev
(models, ORM) |

Severity: Normal | Resolution: wontfix

Keywords: | Triage Stage:
| Unreviewed
Has patch: 0 | Needs documentation: 0
Needs tests: 0 | Patch needs improvement: 0
Easy pickings: 0 | UI/UX: 0
-------------------------------------+-------------------------------------

Changes (by Sarah Boyce):

* resolution: => wontfix
* status: new => closed

Comment:

Thank you for your suggestion! When suggesting a new feature for Django,
the feature idea should first be proposed and discussed with the
community. To do that, please raise this on the [https://github.com/django
/new-features/issues ​new feature tracker].

I'll close the ticket for now, but if the community agrees with the
proposal, please return to this ticket and reference the feature tracker
discussion so we can re-open it. For more information, please refer to
[https://docs.djangoproject.com/en/stable/internals/contributing/bugs-and-
features/#requesting-features the documented guidelines for requesting
features].

Thanks!
--
Ticket URL: <https://code.djangoproject.com/ticket/36517#comment:2>