AI/ML in Database
Oracle Labs advances Oracle Database with AI/ML, including vector search, in-database models, and graph analytics, empowering enterprises to gain powerful, secure, scalable AI insights in-database.
AI/ML in Database
AI/ML in Database
Oracle Labs advances Oracle Database with AI/ML, including vector search, in-database models, and graph analytics, empowering enterprises to gain powerful, secure, scalable AI insights in-database.
Project Overview
Oracle Labs is advancing AI/ML integration within Oracle Database, focusing on three key areas: enhancing the performance and transactional consistency of vector similarity search indexes; enabling near/in-database execution of ML and LLM models for secure, efficient generative AI workloads at scale; and advancing large-scale SQL graph processing, including natural language-based graph queries and graph-powered RAG pipelines. By tackling these challenges, our research aims to deliver robust, scalable AI/ML capabilities natively within Oracle Database, empowering enterprises to harness advanced AI analytics and insights securely and efficiently, without moving data outside the database environment.
I am working on bringing latest research innovation into core Oracle products. My main focus is on adding support for Operational Property Graph and AI Vector Search inside Oracle database. One of our most recent achievements is that starting 23c release, Oracle will have support for creating and querying property graphs directly in SQL and very efficient vector similarity search queries
Specialties:
- System Architecture
- Databases
- Distributed Systems
- AI and Machine Learning
- Project management
- Research