Object Relational Mapping in Distributed Data Grids
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Solution Overview
Problem
Traditional database storage systems lack distribution, scalability, and high availability, making them unsuitable for cloud computing environments where data as a service (DaaS) is required, as they are stateful and do not scale linearly with the addition or removal of nodes, impacting elasticity and availability.
Innovation Solution
A data grid system that performs object relational mapping by dividing objects into key-value pairs and distributing them across multiple nodes, enabling stateful data to be maintained in a reliable, highly available, and scalable manner, using a distributed data store that can handle dynamic node additions and removals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional database storage systems are used, then data can be stored with structured query capabilities, but the system lacks distribution, scalability, and high availability
Solution Approach 1:
The patent segments the database system into multiple independent nodes forming a distributed data grid. Each node stores portions of the data and can operate independently, enabling the system to maintain high availability even when individual nodes fail. This segmentation transforms a single-point-failure architecture into a fault-tolerant distributed system.
Solution Approach 2:
The patent introduces an object-relational mapping layer as an intermediary between the application and the distributed data grid. This mapping layer translates traditional database operations into data grid operations, allowing applications to access distributed storage without needing to understand the underlying complexity, thus improving availability while managing system complexity.
2Productivity
If databases run on a single machine or fixed cluster, then data storage is simple to manage, but the system does not scale linearly with node additions
Solution Approach 1:
The patent implements a dynamic distributed data grid where nodes can be added or removed without reconfiguring the entire system. The data grid automatically redistributes data and maintains consistency when nodes join or leave the network, enabling linear scalability while managing dynamic node complexity through automated algorithms.
Solution Approach 2:
The patent creates a universal data storage system that can function both as a traditional database for structured queries and as a distributed key-value store for high-performance operations. This multi-functionality allows the system to scale across different workloads and node configurations without requiring separate systems, improving productivity while managing complexity through a unified architecture.
3Adaptability or versatility
If databases are not distributed by nature, then data storage is consistent and reliable, but elasticity and high availability are hampered
Solution Approach 1:
The patent implements feedback mechanisms in the distributed data grid where nodes continuously exchange state information and coordinate data operations. This feedback loop ensures that data consistency is maintained across distributed nodes while allowing the system to adapt to dynamic conditions, resolving the contradiction between elasticity and information integrity through continuous coordination.
Solution Approach 2:
The patent employs preliminary actions by pre-establishing data replication and consistency protocols before data operations occur. When nodes are added or removed, the system proactively redistributes data and updates consistency metadata in advance, ensuring that elasticity operations do not compromise data integrity and that the system remains adaptable while preserving information consistency.
Data Source
AI summary
A node in a data grid receives a client request to store an object in a database, the request including the object. The node divides the object into a plurality of key value pairs and links the plurality of key value pairs. The node then stores the plurality of key value pairs in the data grid.