External Backup Query Processing for Non-Relational Databases
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Solution Overview
Problem
Running analytics on non-relational database systems poses a challenge due to the impact on processing capacities, as existing methods often require creating and maintaining separate copies of data, which can be costly and inefficient.
Innovation Solution
Implementing external query management and backup management techniques that allow queries to be performed via a database backup hosted in external storage, separating analytical workloads from transactional workloads while maintaining data freshness and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If analytics queries are run on the non-relational database directly, then analytical capabilities are achieved, but the processing capacity of the database is consumed and performance is impacted
Solution Approach 1:
The patent segments the database workload into two separate systems: a non-relational database for transactional operations and an analytical database for query processing. This segmentation allows each system to be optimized for its specific function, preventing analytical queries from consuming transactional processing capacity while maintaining full analytical capabilities.
Solution Approach 2:
The patent creates a copy of the non-relational database structure and stores it in an analytical database. This copy enables analytical queries to be executed without accessing the original transactional database, thus separating workloads. The copy maintains the necessary data structure and relationships to support analytical processing while isolating it from transactional operations.
2Ease of operation
If separate copies of data are created for analytics, then analytical workloads are separated from transactional workloads, but storage costs and system complexity increase
Solution Approach 1:
The patent employs a universal data format that serves both the non-relational database for transactional operations and the analytical database for query processing. This multi-functional approach eliminates the need for separate data formats or complex synchronization mechanisms, reducing system complexity while maintaining effective workload separation.
Solution Approach 2:
The patent introduces an intermediary layer that handles data synchronization between the non-relational database and the analytical database. This intermediary manages the complexity of data replication and ensures that the analytical database receives updated data without requiring direct complex interactions between the two systems, simplifying the overall architecture.
3Productivity
If a backup of the database is used for queries, then database capacity is not consumed, but data freshness may be compromised
Solution Approach 1:
The patent implements preliminary actions by continuously maintaining an updated copy of the database in the analytical database before queries are executed. This pre-updated copy ensures that when analytical queries run, they access the most recent data available, eliminating freshness concerns while preserving database capacity for transactional operations.
Data Source
AI summary
Queries may be made against a non-relational database without impacting the capacities of the non-relational database by enabling performance of queries to a non-relational database via an external query management, backup management, and a non-relational database backup hosted in an external data storage. The query management and backup management of the non-relational database service may split transactional load to the non-relational database and analytical load, and furthermore allow selection of a desired data freshness for queries including various time ranges, such as seconds, minutes, or days.