Graph Database Caching in Federated Systems
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Solution Overview
Problem
Federated database systems face inefficiencies in responding to database queries, particularly for frequently executed queries that require data from multiple sources, as they often involve time-consuming data retrieval and integration processes.
Innovation Solution
The integration of a graph database within the federated system to cache retrieved data and relationships, allowing for faster response to subsequent queries by leveraging cached data instead of re-retrieving from source databases, along with the use of a virtual relationship table to define and manage relationships among objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is retrieved from multiple autonomous data sources in a federated database system, then data completeness and accuracy are improved, but query response time deteriorates due to time-consuming data retrieval and integration processes
Solution Approach 1:
The patent implements a caching mechanism that pre-retrieves and stores data from autonomous data sources in a cache database before queries are executed. When a query is received, the system first checks the cache for relevant data, retrieving it instantly without needing to access the original data sources. This preliminary action of caching data resolves the contradiction by providing complete data (maintaining reliability) while eliminating the time-consuming retrieval process (improving response time).
Solution Approach 2:
The patent creates copies of data from autonomous data sources and stores them in a cache database. Instead of querying the original data sources directly, the system queries these cached copies, which provides the same data completeness and accuracy while dramatically reducing query response time since the copies are already available in memory or fast storage.
2Adaptability or versatility
If data from multiple autonomous data sources is integrated into a federated database, then data accessibility and versatility are improved, but system complexity deteriorates due to integration challenges
Solution Approach 1:
The patent introduces a cache database as an intermediary layer between the autonomous data sources and the query interface. This cache database simplifies the system architecture by providing a unified access point that abstracts away the complexity of multiple data sources. The cache database receives queries and returns data without requiring complex integration logic, thus improving data accessibility while reducing system complexity.
Solution Approach 2:
The patent extracts the integration complexity from the core query processing system by implementing a separate caching layer. The cache database handles the complexity of data retrieval and storage independently, allowing the main federated database system to focus on query processing. This separation of concerns reduces overall system complexity while maintaining versatile data access across multiple autonomous sources.
3Quantity of substance
If traditional relational database structures are used, then data storage efficiency is improved, but flexibility in defining relationships among objects deteriorates
Solution Approach 1:
The patent changes the data structure parameter from traditional relational tables to a graph database structure with nodes and edges. This parameter change allows the system to maintain efficient data storage while dramatically improving flexibility in defining relationships. The graph structure enables arbitrary relationship definitions between objects without requiring rigid table schemas or complex join operations, thus resolving the contradiction between storage efficiency and relationship flexibility.
Solution Approach 2:
The patent implements a dynamic data structure using graph databases where relationships between objects can be freely defined and modified. Unlike static relational schemas, the graph structure allows relationships to be created, changed, and deleted dynamically based on query requirements, maintaining storage efficiency while providing maximum flexibility in relationship definition.
Data Source
AI summary
A method includes receiving a database query for a first database and determining whether a second database contains data responsive to the database query, wherein the second database comprises a graph database. The method also includes retrieving responsive data from a memory device associated with the second database if it is determined that the second database contains data responsive to the database query. The method further includes responding to the database query by providing the responsive data.