Canonicalized Table Caching for Low-Latency Database Requests

Solution Overview

Problem

Modern businesses face challenges in efficiently accessing and manipulating large datasets stored in cloud-based data warehouses due to complex queries and high query costs, which often result in latency and inefficiencies.

Innovation Solution

A system that maintains a canonical table repository, transforms retrieved tables into canonicalized versions, and matches user requests against these canonicalized tables to serve data without issuing new database queries, thereby reducing latency and improving efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If complex queries are issued to cloud-based data warehouses, then data access capability is improved, but query cost and latency increase

Engineering Contradiction:

Improvedata access capabilityVSAvoidquery latency

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system performs preliminary actions by caching query results in a local cache before they are needed. When a query is executed against the cloud-based data warehouse, the result is stored in the local cache. Subsequent identical or similar queries can be served from the cache, eliminating the need to re-query the remote database and thus reducing latency while maintaining data access capability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates copies of query results and stores them in a local cache. Instead of repeatedly accessing the remote cloud-based data warehouse, the system serves copied data from local storage. This copying mechanism reduces the time and cost associated with repeated queries while preserving the ability to access the underlying data.

Inventive Principle:

Principle #26Copying

2Ease of operation

If complex queries are issued to cloud-based data warehouses, then data access capability is improved, but query cost increases

Engineering Contradiction:

Improvedata access capabilityVSAvoidquery cost

Core Design Contradiction:

Ease of operationVSLoss of energy

Solution Approach 1:

The system performs preliminary actions by caching query results in a local cache before they are needed. When a query is executed against the cloud-based data warehouse, the result is stored in the local cache. Subsequent identical or similar queries can be served from the cache, eliminating the need to re-query the remote database and thus reducing latency while maintaining data access capability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates copies of query results and stores them in a local cache. Instead of repeatedly accessing the remote cloud-based data warehouse, the system serves copied data from local storage. This copying mechanism reduces the time and cost associated with repeated queries while preserving the ability to access the underlying data.

Inventive Principle:

Principle #26Copying

3Reliability

If queries are issued frequently to cloud-based data warehouses, then data freshness is improved, but system efficiency deteriorates

Engineering Contradiction:

Improvedata freshnessVSAvoidsystem efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary actions by caching query results in a local cache before they are needed. When a query is executed against the cloud-based data warehouse, the result is stored in the local cache. Subsequent identical or similar queries can be served from the cache, eliminating the need to re-query the remote database and thus reducing latency while maintaining data access capability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates copies of query results and stores them in a local cache. Instead of repeatedly accessing the remote cloud-based data warehouse, the system serves copied data from local storage. This copying mechanism reduces the time and cost associated with repeated queries while preserving the ability to access the underlying data.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS12554719B1Servicing database requests using canonicalized tables

Publication Date: 2026.02.17 SIGMA COMPUTING INC

AI summary

Servicing database requests using canonicalized tables including maintaining a canonical table repository of canonicalized tables, wherein each canonicalized table is a transformed version of a table previously retrieved from a database; receiving, from a client computing system, a request for a table from the database; generating a description of a canonical version of the requested table; determining whether the canonical version of the requested table matches a canonicalized table in the canonical table repository; and if the canonical version of the requested table matches the canonicalized table in the canonical table repository: transforming the matching canonicalized table based on the received request for the table; and providing, to the client computing system, the transformed matching canonicalized table.