Database Backup Snapshots for Point-in-Time Cloud Recovery
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Solution Overview
Problem
Existing database backup methods either lack precise point-in-time recovery (non-continuous backups) or do not scale well for large datasets (continuous backups), leading to data inconsistencies or time-consuming recovery processes.
Innovation Solution
A combined approach using continuous replication to a secondary database in a second cloud environment with snapshotting capabilities, allowing for both strong data consistency and point-in-time recovery by capturing and storing snapshots at defined intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous backup is used, then data consistency and fast recovery are improved, but resource consumption and complexity increase
Solution Approach 1:
The backup system is segmented into two distinct components: continuous replication for maintaining data consistency and periodic snapshots for point-in-time recovery. This segmentation allows each component to specialize in one function, reducing overall system complexity while maintaining the benefits of continuous backup.
Solution Approach 2:
The patent merges continuous replication and periodic snapshots into a unified backup architecture. The secondary database receives both continuous replication streams and periodic snapshot captures, combining the strengths of both approaches to achieve both data consistency and point-in-time recovery capabilities.
2Use of energy by moving object
If non-continuous backup is used, then resource consumption is reduced, but data loss and recovery time increase
Solution Approach 1:
Periodic snapshots are captured in advance at scheduled intervals, preparing point-in-time recovery states before they are needed. This preliminary action ensures that recovery can be quickly performed by restoring to the most recent appropriate snapshot without requiring full database restoration.
Solution Approach 2:
The system implements periodic snapshot capture at defined intervals, creating a series of time-stamped recovery points. This periodic action balances resource consumption with recovery capabilities, allowing the system to maintain multiple recovery states without the continuous resource overhead of pure continuous backup.
3Measurement precision
If continuous replication is used, then point-in-time recovery precision is improved, but scalability is reduced
Solution Approach 1:
The recovery precision function is segmented from the continuous replication stream and handled by periodic snapshots. This allows the system to scale the snapshot frequency independently of the replication rate, improving scalability while maintaining point-in-time recovery precision through the segmented architecture.
Solution Approach 2:
Instead of continuously capturing and managing every possible recovery point, the system takes periodic snapshots at sufficient intervals to meet recovery requirements. This partial action approach provides adequate point-in-time recovery precision without the excessive resource management overhead of continuous recovery point tracking.
Data Source
AI summary
Computer-implemented methods for managing the backup of a database are provided. Aspects include receiving, by a secondary database stored in a second cloud environment, a continuous replication of a primary database stored in a first cloud environment, instructing a file system of the second cloud environment to capture a snapshot of the secondary database, and transmitting the snapshot to a data storage system for storage. The file system of the second cloud environment utilizes logical volume management.