Hybrid Database Execution Switching for SME Scalability
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Solution Overview
Problem
Existing database solutions fail to provide optimal performance for small and medium-sized enterprises, as mainstream distributed databases are inefficient in stand-alone environments, while stand-alone databases face challenges with data migration and scalability as enterprises grow.
Innovation Solution
A hybrid database architecture that dynamically switches between stand-alone and distributed modes, using serial or parallel execution based on data volume and location, with local or distributed execution methods, and local or distributed parallelism to optimize performance and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a distributed database is used, then fault tolerance and horizontal scalability are improved, but performance in small-scale environments deteriorates due to intricate internal architecture
Solution Approach 1:
The database system dynamically switches between distributed mode and stand-alone mode based on enterprise scale and workload requirements. This dynamic adaptation allows the system to leverage distributed architecture benefits (fault tolerance, scalability) when needed while avoiding its overhead in small-scale environments, thus resolving the contradiction between reliability improvement and performance deterioration.
2Productivity
If a stand-alone database is used, then performance for small and medium-sized enterprises is improved, but scalability and data migration flexibility deteriorate as enterprises grow
Solution Approach 1:
The system transitions from stand-alone mode to distributed mode as enterprises grow, providing seamless scalability. This dynamic mode switching enables the database to maintain optimal performance in small-scale environments while automatically adapting to support larger enterprises, thus resolving the contradiction between performance and scalability.
Solution Approach 2:
The hybrid database architecture serves multiple functions across different enterprise scales. It can operate as a stand-alone database for small and medium-sized enterprises while also functioning as a distributed database for large enterprises, making it universally applicable and eliminating the need for database replacement during growth.
3Adaptability or versatility
If a hybrid database architecture is implemented, then adaptability to different enterprise sizes is improved, but device complexity increases
Solution Approach 1:
The complexity management is achieved through dynamic mode switching. When operating in stand-alone mode, the system presents a simple interface despite having distributed capabilities available. The complex distributed architecture is only activated when needed, reducing the perceived complexity for users while maintaining adaptability.
Data Source
AI summary
Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for data request processing. In an example method, a system receives a data request that queries data stored in one or more nodes of the system. The system determines, based at least on a data volume of the queried data, whether to process the data request using serial execution or parallel execution. In response to determining to use serial execution, the system dynamically processes the data request, using one of a local execution method, a remote execution method, or a distributed execution method. In response to determining to use parallel execution, the system dynamically processes the data request using one of a local parallelism method or a distributed parallelism method.