This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Databricks Inc.. Active years: 2025.
Company Filing History:
Years Active: 2025
Title: Gengliang Wang: Innovator in Database Query Error Attribution
Introduction
Gengliang Wang is a notable inventor based in San Francisco, CA. He has made significant contributions to the field of database management through his innovative patent. His work focuses on improving the reliability and efficiency of database queries, which is crucial for developers and organizations that rely on data-driven decision-making.
Latest Patents
Gengliang Wang holds a patent titled "Runtime error attribution for database queries specified using a declarative database query language." This patent addresses the challenges faced during the execution of database queries, particularly those specified using structured query language (SQL). The system he developed identifies runtime errors, such as division by zero or resource usage errors, and reports the origins of these errors. By pinpointing the specific portions of a database query that cause runtime errors, his invention simplifies the development and testing processes for database queries. He has 1 patent to his name.
Career Highlights
Gengliang Wang is currently employed at Databricks Inc., a company known for its advanced data analytics and machine learning solutions. His role at Databricks allows him to leverage his expertise in database technologies and contribute to innovative solutions that enhance data processing capabilities.
Collaborations
Some of Gengliang's coworkers include Wenchen Fan and Serge Rielau. Their collaboration fosters a creative environment that encourages the development of cutting-edge technologies in the field of data management.
Conclusion
Gengliang Wang's contributions to database query error attribution represent a significant advancement in the field of data management. His innovative patent not only addresses critical issues faced by developers but also enhances the overall efficiency of database systems.
