Oracle Labs research is focused on real-world outcomes: our researchers aim to develop technologies that will someday play a significant role in the evolution of technology and society.
Distributed Systems Group
Research project to explore distributed computing problems relevant to Big Data Analytics, Cloud Infrastructures and modern networking and storage technologies.
KeyBridge is a multi-disciplinary project using expertise from systems-programming, data visualization and machine learning in order to understand massive streams of data.
Machine Learning Research Group
The mission of the Machine Learning Research Group is to scale Machine Learning across Oracle by researching and developing ML-based solutions that improve Oracle's products and services.
Parallel Graph AnalytiX (PGX)
Parallel, efficient, in-memory, single-machine and distributed graph processing
Programming Language Research Group
Programming language design, semantics, algorithms, and implementation with an emphasis on convenient use of parallelism using multicores and GPUs.
Randomized Decomposition is a mathematical programming technique for solving hard, non-convex mathematical programming problems.
Exploration of new secure language concepts and secure abstractions that can be applied in future languages to prevent vulnerabilities in code written in those languages.
Automated Machine Learning and ML Explainability
This project is building an advanced pipeline for automating machine learning, including model selection, feature selection, hyperparameter tuning and model explainability.
Computer Architecture and Performance Modeling (CAP)
Performance analysis of computer system architectures exploiting new technology trends using advanced workload characterization and modeling techniques.
Domain Global Graphs
Integrates PGX & Data Studio into solutions that investigate domain graphs, e.g., in Oracle Financial Services Crime & Compliance Studio, and researches improvements, e.g., by using Machine Learning.
Intelligent Application Security (IAS)
The Intelligent Application Security team at Oracle Labs works on innovative projects in the application security space spanning areas like program analysis and machine learning.
Machine Learning on Graphs
This project focuses on developing machine learning techniques and its applications over graph-structured data across multiple domains like cybersecurity, compliance, healthcare and recommenders.
Native Graph Support in Oracle Autonomous Database
The project aims at bringing state-of-the-art scalable graph analytical technologies into Oracle Autonomous Database.
Open Source Intelligence (OSInt)
OSInt is a program analysis/big data analytics project that aims to gather information about vulnerabilities in third party libraries from various sources on the internet.
Oracle Database Multilingual Engine
A runtime for executing GraalVM languages in Oracle Database.
Oracle Labs Apps
Designing, building and operating modern apps running on Oracle Cloud Infrastructure
Oracle Labs Data Studio
A multi-tenant, multi-server, scalable and secure arbitrary code execution engine with a notebook frontend.
Project RASPunzel aims to deliver an automated and scalable runtime application self-protection (RASP) solution for Java.
Introduce self-optimization capabilities into Oracle's computer systems and processes based on adaptive learning methods
Affogato is a dynamic taint analysis engine for Node.js.
The Callisto project investigates how systems software can evolve to better support parallel and distributed runtime systems on tightly-coupled clusters and on large NUMA systems.
CAD system with schematic capture and layout features.
FastR is an open-source high-speed implementation of the R programming language for statistics atop Truffle and Graal.
A tool that lets you query a graph of extracted code dependencies to find symbols, show references, follow chains and determine the impact of changes to your multimillion-line codebase.
Oracle's meta-circular research VM written in Java.
Static program analysis techniques focusing on developing precise and scalable analyses for finding bugs in large-scale C and C++ source code.
Research project exploring potential effects of emerging byte-addressable persistent memory technologies on software and systems design.
We are passionate about improving the quality of software and the productivity of developers.
RAPID provides a scale out architecture for providing very high performance for SQL analytics. This technology has been optimized for OCI Gen 2 and will be available as MySQL analytics service
Principles and techniques for developing concurrent programs that are scalable, efficient, and correct.
Research in photonics, interconnects and advanced packaging for advanced computing platforms.
Develops high-speed circuit technologies and design methods that enable novel architectures.