Dynamic Chronometry Data Orientation for Low-Latency Database Analysis
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Solution Overview
Problem
Existing database analytic tools are inefficient, costly, and require substantial configuration and training due to the complexity of large volumes of data stored in relational database systems, which limits accessibility and the ability to identify useful data patterns.
Innovation Solution
Implementing dynamic chronometry data orientation in a low-latency database analysis system, allowing for the use of domain-specific chronometry datasets in addition to system-defined chronometry, enabling efficient representation and analysis of temporal data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing database analytic tools are used to analyze large volumes of data, then data analysis can be performed, but the tools are inefficient, costly, and require substantial configuration and training
Solution Approach 1:
The patent segments the monolithic database analysis system into distinct functional layers: data ingestion layer, processing layer, and output layer. This segmentation allows each layer to be optimized independently, reducing overall system complexity while maintaining analysis capabilities. The processing layer is further divided into separate computation and storage components, enabling specialized optimization for each function.
Solution Approach 2:
The patent introduces an intermediary processing layer between the raw data and the analysis tools. This intermediary layer pre-processes and structures data into standardized formats, reducing the configuration burden on end-user tools. The intermediary acts as a mediator that translates complex database operations into simpler, more accessible queries for end users.
2Quantity of substance
If relational database systems store large volumes of data, then data capacity increases, but access and pattern identification become less efficient
Solution Approach 1:
The patent transitions from traditional two-dimensional relational table structures to a multi-dimensional data model that incorporates hierarchical, network, and temporal dimensions. This dimensional expansion allows data to be organized and accessed along multiple axes simultaneously, improving query efficiency for complex analytical operations while maintaining large storage capacity.
Solution Approach 2:
The patent changes fundamental data organization parameters by implementing columnar storage instead of row-based storage, and by using variable-length data structures with dynamic compression. These parameter changes enable more efficient data compression ratios and faster selective data access, directly improving productivity without sacrificing storage capacity.
3Quantity of substance
If traditional database tools are used, then data can be stored, but the tools are costly to utilize
Solution Approach 1:
The patent implements self-service capabilities where the database system automatically performs data optimization, query planning, and resource allocation without requiring expensive external consulting or extensive administrator intervention. The system includes built-in automated tuning mechanisms that adapt to usage patterns, reducing operational costs while maintaining storage capabilities.
Solution Approach 2:
The patent creates a universal database platform that consolidates multiple specialized tools into a single system. The platform can handle various data types, perform multiple analysis functions, and serve different user roles through a unified interface. This multi-functionality eliminates the need for separate specialized tools, reducing overall utilization costs while preserving comprehensive data storage and analysis capabilities.
Data Source
AI summary
Operating a low-latency database analysis system using domain-specific chronometry may include obtaining, in the low-latency database analysis system, data expressing a usage intent with respect to the low-latency database analysis system, in response to obtaining the data expressing the usage intent, obtaining ontological data for a chronometric object in the low-latency database analysis system indicated by the data expressing the usage intent, identifying a chronometry dataset from a plurality of chronometry datasets, wherein the plurality of chronometry datasets includes a domain-specific chronometry dataset and a canonical chronometry dataset, obtaining results data in accordance with the chronometry dataset and the chronometric object, generating output data representing the results data in accordance with the chronometry dataset, and outputting the output data for presentation via a user interface.