Santa Clara, CA, United States of America

Boyang Peng

USPTO Granted Patents = 1 

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Boyang Peng: Innovator in Database Query Processing

Introduction

Boyang Peng is a notable inventor based in Santa Clara, CA (US). He has made significant contributions to the field of database systems, particularly in the area of processing streaming data. His innovative approach has led to advancements that enhance the efficiency of database query execution.

Latest Patents

Boyang Peng holds a patent for "Pipelined execution of database queries processing streaming data." This patent describes a database system that performs pipelined execution of queries that process batches of streaming data. The system compiles a database query to generate an execution plan and determines a set of stages based on this plan. It processes streaming data in batches and schedules the execution stages in a manner that allows for parallel processing. The system also maintains watermarks for different stages of the database query, ensuring efficient management of data flow.

Career Highlights

Boyang Peng is currently associated with Databricks Inc., a company known for its innovative data and AI solutions. His work at Databricks focuses on enhancing database systems and improving the performance of data processing tasks. His contributions have been instrumental in advancing the capabilities of modern database technologies.

Collaborations

Boyang has collaborated with notable colleagues, including Michael Paul Armbrust and Alexander Balikov. These collaborations have fostered an environment of innovation and have led to the development of cutting-edge solutions in the field of data processing.

Conclusion

Boyang Peng's work in database query processing exemplifies the impact of innovation in technology. His patent and contributions to Databricks Inc. highlight his role as a key figure in advancing database systems for streaming data.

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