Company Filing History:
Years Active: 2021-2023
Title: Niv Dayan: Innovator in Key-Value Store Technologies
Introduction
Niv Dayan is a prominent inventor based in Somerville, MA (US). He has made significant contributions to the field of data storage and retrieval, holding a total of 5 patents. His work focuses on optimizing key-value stores and enhancing statistical analysis methods.
Latest Patents
One of Niv Dayan's latest patents is centered around key-value stores with optimized merge policies and optimized LSM-tree structures. This invention utilizes an improved LSM-tree-based key-value approach to strike the optimal balance between the costs of updates, lookups, and storage space. The improved approach involves a new merge policy that minimizes merge operations to only the largest levels of the LSM-tree. Additionally, it allows for separate control over the frequency of merge operations for different levels, maximizing throughput for specific workloads.
Another notable patent involves systems and methods for accelerating exploratory statistical analysis. This invention employs a 'data canopy' that simplifies statistical measures into basic primitives for various data portions. These basic aggregates are stored in a library within an in-memory data structure, allowing for efficient reuse in statistical computations when queried measures overlap with stored aggregates.
Career Highlights
Niv Dayan is currently associated with Harvard College, where he continues to innovate and contribute to advancements in data management technologies. His work has garnered attention for its practical applications in improving data processing efficiency.
Collaborations
Niv has collaborated with notable colleagues, including Stratos Idreos and Wasay Abdul, who share his passion for advancing technology in data storage and analysis.
Conclusion
Niv Dayan's contributions to the field of key-value stores and statistical analysis exemplify his innovative spirit and dedication to improving data management technologies. His patents reflect a commitment to enhancing efficiency and effectiveness in data processing.