Quantum Database Backup Scaling for Fast Critical Data Recovery

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Solution Overview

Problem

Existing database backup and recovery systems experience significant delays, causing financial and physical harm due to data access and restoration challenges during outages or data loss, especially for critical data.

Innovation Solution

A quantum-computing-powered system with multi-dimensional scaling, incorporating a classical processor and quantum processor, ML engine, and cloud-based databases, enables efficient backup and restoration by routing search queries and data restoration through quantum processors, and dynamically scaling quantum resources based on task duration and volume.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data is backed up in traditional database systems, then data redundancy is achieved, but data access and restoration experience considerable delays

Engineering Contradiction:
Improvedata backup reliabilityVSAvoiddata restoration time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces traditional classical computing systems with quantum computing systems for database backup and restoration operations. Quantum processors leverage quantum mechanical phenomena (superposition, entanglement, interference) to perform parallel computations exponentially faster than classical systems, dramatically reducing data restoration time while maintaining backup reliability

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system implements dynamic scaling of quantum computing resources based on workload demands. The quantum processor can scale from a default number of quantum threads and circuits to additional threads and circuits when processing tasks exceed threshold durations or volumes, optimizing both speed and resource efficiency for time-critical restoration operations

Inventive Principle:
Principle #15Dynamics

2Speed

If quantum processor resources are increased to speed up processing, then processing speed improves, but system complexity and resource management difficulty increase

Engineering Contradiction:
Improveprocessing speedVSAvoidquantum processor complexity
Core Design Contradiction:
SpeedVSDevice complexity

Solution Approach 1:

The system implements dynamic scaling of quantum computing resources based on workload demands. The quantum processor can scale from a default number of quantum threads and circuits to additional threads and circuits when processing tasks exceed threshold durations or volumes, optimizing both speed and resource efficiency

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system continuously monitors processing task performance metrics (duration and volume) and uses this feedback to automatically scale quantum processor resources. When tasks exceed predefined thresholds, the system adds quantum threads and circuits; when tasks are completed, resources are scaled back, creating a self-regulating system that balances speed with complexity management

Inventive Principle:
Principle #23Feedback

3Reliability

If all data is backed up to ensure complete recovery, then data recovery completeness is improved, but storage requirements and processing overhead increase

Engineering Contradiction:
Improvedata recovery completenessVSAvoidstorage volume
Core Design Contradiction:
ReliabilityVSQuantity of substance

Solution Approach 1:

The system extracts and prioritizes only the most critical data subsets for quantum-accelerated backup and restoration operations. By identifying and separating critical data from non-critical data, the system achieves rapid recovery of essential information without the storage and processing overhead of backing up entire databases

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The system applies different backup and restoration strategies to different data subsets based on their criticality. Critical data receives priority quantum-accelerated processing with guaranteed recovery SLAs, while non-critical data uses traditional backup methods, optimizing both recovery completeness and resource utilization

Inventive Principle:
Principle #3Local quality

Data Source

PatentUS12566992B2Quantum-computing-powered system with multi-dimensional scaling for database backup, search, and recovery
Publication Date: 2026.03.03 BANK OF AMERICA CORP
  • US12566992B2 patent drawing
  • US12566992B2 patent drawing
  • US12566992B2 patent drawing

AI summary

A method for database backup, search, and recovery using a quantum-computing-powered system with multi-dimensional scaling is provided. The method may include storing a first dataset in a first local database, generating a second dataset from a critical subset of the first dataset, and storing the second dataset in a second remote, cloud-based, database. The method may include receiving a search query at the first database. The method may include receiving a first indication of an outage at the first database and, in response to the first indication, routing the search query to a quantum processor and executing the search on the second dataset. The method may include receiving a second indication of a loss of data from the first dataset at the first database, and, in response to the second indication, restoring the critical subset of the first dataset to the first database from the second dataset at the second database using the quantum processor. The method may include automatically scaling the quantum processor during a processing task.