Hybrid Data Retention Across SQL and NoSQL Databases
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Relational database systems face scalability limits when managing large volumes of data, making them less effective in environments requiring flexible data management, such as on-demand services and multitenant databases.
Innovation Solution
Data is selectively retained in a non-relational database like Apache HBase, with transfer triggered by preselected conditions, and SQL queries are translated into native NoSQL store APIs for efficient data management and access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If relational database systems are used to store large amounts of data, then data structure and query capability are maintained, but scalability limits are reached and system effectiveness decreases
Solution Approach 1:
The patent divides the database system into two distinct parts: a relational database for structured data and queries, and a non-relational database for large-scale data storage. This segmentation allows each database type to operate within its optimal performance range, resolving the scalability limitation of relational databases while maintaining data structure requirements.
Solution Approach 2:
The patent introduces a data transfer mechanism as an intermediary between the relational and non-relational databases. This intermediary component handles the data migration and synchronization, enabling the system to leverage the scalability of non-relational databases while maintaining the structured query capabilities of relational databases.
2Adaptability or versatility
If data is stored in a non-relational database for scalability, then horizontal scalability and access characteristics improve, but data structure and query translation complexity increase
Solution Approach 1:
The patent employs a query translation layer as an intermediary that converts SQL queries into native NoSQL store APIs. This intermediary component abstracts the complexity of query translation from the user interface, allowing simple SQL queries to leverage the scalability of non-relational databases without exposing the underlying complexity.
Solution Approach 2:
The patent creates a virtual copy of the relational database interface that maps to the non-relational database storage. This copying approach allows the system to present a familiar relational interface while backing it with the scalable non-relational storage, thereby achieving scalability without increasing user-facing complexity.
3Adaptability or versatility
If data transfer between relational and non-relational databases is implemented, then scalability is achieved, but data retention and transfer management complexity increase
Solution Approach 1:
The patent implements preselected conditions that trigger data transfer from the relational to the non-relational database before scalability issues arise. This preliminary action approach proactively manages data retention by transferring data at optimal times, reducing the complexity of real-time data management while maintaining scalability.
Data Source
AI summary
Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.