Multi-Cluster Database Data Distribution Service
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional NoSQL databases face challenges in evenly distributing data across multiple clusters, leading to overloading and underutilization, which affects responsiveness and resource efficiency, and require complex modifications to manage cluster changes, increasing the risk of downtime and data inconsistency.
Innovation Solution
A multi-cluster database management system that uses cluster partitions to evenly distribute data across clusters, allowing for efficient addition or removal of clusters without modifying client applications, and ensures data availability by redistributing data across clusters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is distributed across multiple clusters in conventional NoSQL databases, then the database can accommodate larger amounts of data, but the data cannot be evenly distributed leading to overloading of some clusters and underutilization of others
Solution Approach 1:
The patent introduces a data distribution service as an intermediary component that manages data placement across clusters. This service receives data write requests, determines the optimal target cluster based on current cluster states, and routes the data accordingly. This intermediary layer abstracts the complexity of multi-cluster data distribution from client applications while maintaining balanced load distribution across clusters.
2Quantity of substance
If multiple clusters are used to accommodate larger datasets, then storage capacity increases, but the complexity of managing cluster additions and removals increases requiring application modifications
Solution Approach 1:
The data distribution service automatically detects when clusters are added or removed from the database system and dynamically adjusts data distribution without requiring application modifications. The service monitors cluster states, performs rebalancing operations, and manages data migration automatically, allowing the system to adapt to changing infrastructure while maintaining transparency to client applications.
3Adaptability or versatility
If conventional databases allow servers to be added or removed from clusters, then resource allocation flexibility improves, but rebalancing data becomes time-consuming and inefficient
Solution Approach 1:
The data distribution service maintains real-time knowledge of cluster states and data locations, enabling it to perform preliminary assessments before rebalancing operations. When clusters are added or removed, the service can quickly determine optimal data placement strategies and execute rebalancing operations efficiently, minimizing downtime and avoiding time-consuming manual intervention.
4Adaptability or versatility
If client-side application sharding is used to distribute data between clusters, then multiple clusters can be utilized, but additional code is required increasing debugging and maintenance effort
Solution Approach 1:
The patent extracts the data distribution logic from client applications and consolidates it into a dedicated data distribution service. This service handles all decisions regarding which cluster should receive or provide data, removing the need for applications to contain sharding logic. The extraction of this complexity reduces application code while centralizing distribution intelligence in a manageable service component.
Data Source
AI summary
A multi-cluster database management system is disclosed that distributes and manages data across a multi-cluster database through the use of cluster partitions. The multi-cluster database management system assigns cluster partitions to clusters of the multi-cluster database. The multi-cluster database management system can evenly or substantially evenly divide the cluster partitions and associated data among the clusters of the multi-cluster database. The multi-cluster database management system can scale in or out by adding or removing clusters from the multi-cluster database when needed or desired. Once a cluster is added or removed, the multi-cluster database management system re-balances the cluster partitions and the associated data across the clusters of the modified multi-cluster database.