You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
Repository navigation
Python: feat(oracle): add new Oracle connector for Semantic Kernel - #13229
This change is required to enable Semantic Kernel users to store and retrieve embeddings using Oracle databases. Currently, Semantic Kernel supports vector storage for several backends, but Oracle was missing. This connector solves that gap by providing full async support, native VECTOR type handling, and vector index management.
Description
This PR introduces a new Oracle connector for Semantic Kernel with the following features:
Asynchronous upsert, get, delete and search operations for memory records.
Native Oracle VECTOR type support for storing embeddings efficiently.
Support for HNSW and IVFFLAT vector indexes for similarity search.
Integration with Semantic Kernel collections, enabling semantic search and memory operations.
Comprehensive unit tests to ensure correctness and stability.
The connector is designed to work seamlessly with existing Semantic Kernel memory abstractions and follows the same async patterns as other vector stores.
Integration tests have also been implemented and verified locally; however, they are not included in this PR because the current CI environment setup for Oracle Database support is unknown.
Once guidance is provided on Oracle DB availability in the CI pipeline, integration tests can be enabled and added in a follow-up PR.
Contribution Checklist
The code builds clean without any errors or warnings
Monita (@monita1208) please read the following Contributor License Agreement(CLA). If you agree with the CLA, please reply with the following information.
(default - no company specified) I have sole ownership of intellectual property rights to my Submissions and I am not making Submissions in the course of work for my employer.
@microsoft-github-policy-service agree
(when company given) I am making Submissions in the course of work for my employer (or my employer has intellectual property rights in my Submissions by contract or applicable law). I have permission from my employer to make Submissions and enter into this Agreement on behalf of my employer. By signing below, the defined term “You” includes me and my employer.
Monita (@monita1208) please read the following Contributor License Agreement(CLA). If you agree with the CLA, please reply with the following information.
(default - no company specified) I have sole ownership of intellectual property rights to my Submissions and I am not making Submissions in the course of work for my employer.
@microsoft-github-policy-service agree
(when company given) I am making Submissions in the course of work for my employer (or my employer has intellectual property rights in my Submissions by contract or applicable law). I have permission from my employer to make Submissions and enter into this Agreement on behalf of my employer. By signing below, the defined term “You” includes me and my employer.
github-actionsBot
changed the title
feat(oracle): add new Oracle connector for Semantic Kernel
Python: feat(oracle): add new Oracle connector for Semantic Kernel
Nov 4, 2025
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
msft.ext.vectordataRelated to Microsoft.Extensions.VectorDatapythonPull requests for the Python Semantic Kernel
7 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
…ync support
Motivation and Context
This change is required to enable Semantic Kernel users to store and retrieve embeddings using Oracle databases. Currently, Semantic Kernel supports vector storage for several backends, but Oracle was missing. This connector solves that gap by providing full async support, native VECTOR type handling, and vector index management.
Description
This PR introduces a new Oracle connector for Semantic Kernel with the following features:
Asynchronous upsert, get, delete and search operations for memory records.
Native Oracle VECTOR type support for storing embeddings efficiently.
Support for HNSW and IVFFLAT vector indexes for similarity search.
Integration with Semantic Kernel collections, enabling semantic search and memory operations.
Comprehensive unit tests to ensure correctness and stability.
The connector is designed to work seamlessly with existing Semantic Kernel memory abstractions and follows the same async patterns as other vector stores.
Integration tests have also been implemented and verified locally; however, they are not included in this PR because the current CI environment setup for Oracle Database support is unknown.
Once guidance is provided on Oracle DB availability in the CI pipeline, integration tests can be enabled and added in a follow-up PR.
Contribution Checklist