Interactive Search Paths for Relational Database Querying
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Solution Overview
Problem
Current database systems face challenges such as complexity in setup and maintenance, inefficiencies in handling large datasets, and difficulties in scaling, particularly with relational databases, object databases, and graph databases, which often require locking database structures during modifications, leading to performance issues and data integrity threats.
Innovation Solution
A method and system for data analysis in relational databases that allows users to explore and analyze data objects through an interactive data discovery and visualization tool, enabling non-hierarchical data storage and query processes, where filtering operations generate filtered datasets and visual graphical elements to guide users through incremental steps without requiring SQL knowledge, and optimizing data partitioning across compute resources to handle complex connections efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If database structures are locked during modifications, then data integrity is maintained, but query performance deteriorates and processing time increases
Solution Approach 1:
The patent divides the database into multiple partitions that can be independently modified. Each partition can be locked separately during modification, allowing other partitions to remain accessible and continue processing queries. This segmentation resolves the contradiction by maintaining data integrity in modified partitions while preserving query performance in unmodified partitions.
Solution Approach 2:
The patent implements dynamic locking mechanisms where locks are applied only to specific partitions being modified rather than the entire database. The locking scope is adjusted dynamically based on which partitions require modification, allowing the system to adapt between integrity protection and performance requirements in real-time.
2Shape
If relational databases are used, then data structure organization is improved, but setup complexity and maintenance difficulty increase
Solution Approach 1:
The patent implements self-service features where the database system automatically generates and maintains indexes, creates partitioning strategies, and manages metadata without requiring extensive manual configuration. The system serves itself by automatically optimizing its own structure, reducing setup complexity while maintaining organized data storage.
Solution Approach 2:
The patent allows dynamic adjustment of database parameters such as partitioning strategies, index creation, and metadata schemas without requiring complex reconfiguration. Users can modify these parameters through simplified interfaces, changing data organization characteristics without increasing setup complexity.
3Adaptability or versatility
If graph databases are used, then handling complex connections is improved, but scalability and data processing efficiency deteriorate
Solution Approach 1:
The patent segments the graph database into multiple partitions that can be processed independently. Each partition contains a subset of nodes and edges, allowing parallel processing and improving scalability. The graph structure maintains its adaptability for complex connections while being divided into manageable units for efficient processing.
Solution Approach 2:
The patent introduces a partitioning dimension to the graph database structure, organizing data not just by node relationships but also by spatial or categorical partitions. This additional dimension enables efficient data processing by allowing queries to operate on smaller partitions rather than the entire graph, improving productivity while maintaining connection handling capabilities.
4Adaptability or versatility
If database modifications are performed, then schema updates are enabled, but processing time and system performance decrease
Solution Approach 1:
The patent segments database modifications into partition-level operations rather than database-wide operations. Schema updates are applied to specific partitions independently, allowing other partitions to continue processing without interruption. This reduces the overall processing time for schema modifications while maintaining schema flexibility.
Solution Approach 2:
The patent implements preliminary actions by pre-creating partition structures and metadata before modifications are needed. Indexes and partitioning schemes are established in advance, so when modifications occur, the system can apply changes to pre-defined partitions rather than creating structures during processing, reducing processing time.
Data Source
AI summary
A computing system or a method provides a user interface to perform data analysis in a relational database, comprising: (a) bringing an electronic device of a user in communication with a computer server comprising the relational database that stores data objects in a non-hierarchical manner, which electronic device comprises a user interface; (b) receiving a request from the user via the user interface to perform a task directed to at least a subset of the data objects; (c) generating filtering operations for the task, which filtering operations is stored in a memory unit and, upon execution, generates a filtered data set from the subset of the data objects; and (d) automatically generating a search path comprising a plurality of visual graphical elements on the user interface, and the visual graphical elements correspond to the one or more filtering operations.