Unified Database Tool for Operational and Analytical Data
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Solution Overview
Problem
Maintaining two separate databases for operational and analytical data leads to synchronization issues and data quality problems due to redundant data storage, which becomes increasingly difficult as data volume grows.
Innovation Solution
A database tool that enables a single database to store both operational and analytical data by copying operational data into an analytical table, performing statistical analysis, and storing purged data historically, while predicting user access patterns to reduce traffic by caching frequently accessed data in memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If two separate databases are maintained for operational and analytical data, then data access patterns for different user groups can be optimized, but synchronization issues and data quality problems occur due to redundant data storage
Solution Approach 1:
The patent merges operational and analytical databases into a single unified database system. The operational table and analytical table coexist in the same database, sharing common data storage while allowing different access patterns. This eliminates redundant data storage and synchronization issues while maintaining the ability to optimize access for different user groups through table-specific configurations and caching strategies.
Solution Approach 2:
Within the unified database, the system segments data into different tables (operational table and analytical table) with distinct structures and access optimizations. The operational table is optimized for high-traffic customer transactions, while the analytical table is optimized for employee analytics queries. This segmentation allows each table to be tailored to its specific access pattern while avoiding the pitfalls of complete database separation.
2Reliability
If a single database is used for both operational and analytical data, then redundant data storage is eliminated, but different access patterns for customers and employees cannot be optimized
Solution Approach 1:
The patent applies local quality by optimizing specific tables within the unified database for their respective access patterns. The operational table uses configurations suitable for high-traffic customer transactions, while the analytical table uses configurations optimized for employee analytics queries. Each table has tailored access paths, indexing strategies, and caching mechanisms that match its specific usage requirements, allowing the system to maintain data quality while accommodating different access patterns.
3Speed
If frequently accessed data is copied into cache memory, then user access speed is improved, but memory resources are consumed
Solution Approach 1:
The patent implements partial action by caching only the most frequently accessed portions of data in memory, rather than caching entire tables or all data. The system identifies hot data segments that are accessed repeatedly and loads only those into cache memory, leaving less frequently accessed data in the database. This selective caching approach significantly improves query execution time for common operations while conserving memory resources by avoiding unnecessary caching of cold data.
Data Source
AI summary
A memory stores a first cache and a second cache. A processor copies a first portion of data from a first table stored in a database into a second table. The processor further determines that a second portion of data from the first table will be overwritten and copies the second portion into a third table. The processor further determines that a probability that a user will access a third portion of the first table is greater than a threshold and copies the third portion into the first cache. The processor further determines a fourth portion of the first table that the user accesses at a frequency greater than a set frequency and copies the fourth portion into the second cache.