MDM Data Storage via SQL to NoSQL Synchronization
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Solution Overview
Problem
Enterprise-level mobile device management (MDM) platforms face challenges in efficiently storing and analyzing large amounts of data related to managed devices due to the rigid schema of SQL databases, which limits scalability and hinders business intelligence and analytics processing.
Innovation Solution
Implementing a cloud-based infrastructure that synchronizes data from SQL-based databases to schema-less NoSQL databases and special-purpose search engines, allowing for flexible analytics and reporting, using event-driven code execution and services like AWS Lambda for real-time data processing and storage in a scalable manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SQL databases are used for data storage in MDM platforms, then data integrity and fast query processing are improved, but scalability and adaptability to different data structures deteriorate
Solution Approach 1:
The patent segments the database system into multiple specialized components: SQL databases for transactional data integrity, NoSQL databases for scalable unstructured data storage, and search engines for analytics. This segmentation allows each component to optimize for its specific function while collectively providing both reliability and scalability.
Solution Approach 2:
The patent creates a universal data storage architecture that can handle multiple data types and access patterns through different database systems. The system universally supports structured data (SQL), unstructured data (NoSQL), and analytics queries (search engines), making it adaptable to various MDM platform requirements.
2Stability of the object's composition
If SQL databases with rigid schema are used, then data structure organization is improved, but flexibility for analytics processing and scalability deteriorate
Solution Approach 1:
The patent introduces NoSQL databases as an intermediary layer between SQL databases and analytics processing. This intermediary accepts structured data from SQL databases, stores it in a flexible schema-less format, and enables scalable analytics processing without requiring changes to the underlying SQL database structure.
Solution Approach 2:
The patent changes the data storage parameter from fixed schema (SQL) to flexible schema (NoSQL) for analytics workloads. This parameter change allows the system to maintain rigid structure where needed while providing flexibility for analytics processing by storing the same data in different structural formats.
3Adaptability or versatility
If cloud-based infrastructure with NoSQL databases is implemented, then scalability and adaptability are improved, but system complexity increases
Solution Approach 1:
The patent merges multiple database systems (SQL, NoSQL, search engines) into a unified cloud-based infrastructure managed through a single MDM platform interface. This consolidation allows the system to leverage the strengths of each database type while presenting a simplified interface to users, reducing operational complexity despite the multi-component architecture.
Data Source
AI summary
A platform for storing and reporting of data records associated with management of a population of managed devices is disclosed. Data records are injected into a hosted computing environment in which data processing services are arranged to store and generate analytics associated with a mobile device management (MDM) platform.