MongoDB has developed a performance monitoring system for distributed database deployments with dynamic schemas. The system identifies non-optimal implementations in data architecture and models, providing recommendations for resolution. By monitoring database operations and analyzing document samples, the system helps users improve database performance. GlobalData’s report on MongoDB gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on MongoDB, Social media analytics was a key innovation area identified from patents. MongoDB's grant share as of February 2024 was 72%. Grant share is based on the ratio of number of grants to total number of patents.
Performance monitoring system for identifying and resolving database deployment issues
A recently granted patent (Publication Number: US11921744B2) discloses a performance monitoring system designed for distributed database deployments utilizing a dynamic schema to store data in documents organized into collections. The system, operated by at least one processor connected to a memory, is capable of identifying patterns associated with non-optimal implementations within the database deployment. This identification process involves monitoring the operation of the database deployment, sampling documents from collections, and determining if the data meets specific trigger conditions indicating issues with the data architecture or model. The system then generates recommendations for resolving these issues and displays them in a user interface, allowing users to access resolution information.
Furthermore, the system can determine user context for performance analysis based on interactions within the user interface, limiting the data reviewed accordingly. It can also generate data shape information from the stored data while maintaining data secrecy, enabling pattern-based analysis for identifying non-optimal implementations. Additionally, the system can create execution plans to transition the database from a state associated with non-optimal implementation to a state that resolves these issues. By analyzing data within documents and generating collection shapes based on hash values, the system associates performance information with these shapes, providing a comprehensive approach to monitoring and improving database performance in distributed environments.
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