Cache Adapter for Distributed Persistence and SQL Interface

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Solution Overview

Problem

Current cloud computing systems face scalability limitations and high latency due to the inability of relational databases to seamlessly distribute data across physical machine boundaries, and key/value databases struggle with complex object graphs and response time latency.

Innovation Solution

A cache adapter system that communicates with a distributed file system for data persistence and a client cache for synchronization, allowing data to be stored in relational or non-relational formats, and providing a SQL interface for applications, enabling linear scalability and reduced latency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If relational databases are used to store structured data, then data accessibility and robustness are improved, but scalability and network distribution capability deteriorate

Engineering Contradiction:

Improvedata accessibilityVSAvoidscalability

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent introduces a cloud-based data tier with SQL interface that acts as an intermediary between applications and the distributed file system. This intermediary layer provides relational database functionality and SQL querying capabilities while the underlying storage is distributed across the cloud infrastructure, thus maintaining data accessibility without compromising scalability.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent moves the data storage from traditional single-machine relational databases to a cloud-based distributed architecture, adding the dimension of network distribution. This allows data to be accessed through SQL interfaces while being physically distributed across multiple machines and data centers, resolving the contradiction between accessibility and scalability.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Adaptability or versatility

If data is distributed across physical machine boundaries, then scalability is improved, but manual intervention and maintenance complexity increase

Engineering Contradiction:

ImprovescalabilityVSAvoidmaintenance complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The cloud-based data tier automatically manages data distribution, partitioning, and replication across the distributed file system without requiring manual intervention. The system self-adjusts to scaling requirements and handles maintenance operations automatically, thus achieving scalability while reducing maintenance complexity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The cloud-based data tier provides multiple functions including data storage, distribution, replication, and SQL querying through a single unified interface. This multi-functional approach eliminates the need for separate manual management systems for each function, reducing overall maintenance complexity while maintaining scalability.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Adaptability or versatility

If key/value databases are used for distributed storage, then scalability is improved, but response time latency increases

Engineering Contradiction:

ImprovescalabilityVSAvoidresponse time latency

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The patent merges the advantages of key/value databases (distributed storage and scalability) with relational databases (SQL querying and low latency) into a unified cloud-based data tier. This combination allows data to be stored in a distributed manner while providing fast SQL-based access, thus achieving both scalability and low response time latency.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system pre-loads and caches frequently accessed data in the cloud-based data tier, so that when SQL queries are executed, the data is already available in memory rather than needing to be retrieved from distributed storage each time. This preliminary action reduces response time latency while maintaining the scalability benefits of distributed storage.

Inventive Principle:

Principle #10Preliminary action

4Ease of manufacture

If relational databases require structured data format, then data organization is improved, but flexibility to handle complex object graphs deteriorates

Engineering Contradiction:

Improvedata organizationVSAvoidflexibility

Core Design Contradiction:

Ease of manufactureVSAdaptability or versatility

Solution Approach 1:

The cloud-based data tier allows dynamic changes to data schemas and structures through SQL interfaces, enabling flexible handling of complex object graphs while maintaining organized data storage. The system can adapt data models to match application requirements without requiring complete restructuring, thus achieving both data organization and flexibility.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10853306B2Cloud-based distributed persistence and cache data model

Publication Date: 2020.12.01 JADHAV AJAY

AI summary

A distributed cache data system includes a cache adapter configured to reserve a designated portion of memory in at least one node in a networked cluster of machines as a contiguous space. The designated portion of memory forms a cache and the designated portion of memory includes data cells configured to store data. The cache adapter is configured to interface with the data and a distributed file system and the cache adapter is further configured to provide an interface for external clients to access the data. The cache adapter is configured to communicate to clients via a web server, and the cache adapter is further configured to direct data access requests to appropriate the data. A related process of distributing cache data is disclosed as well.