Graph Database Cache and Lookup Table for Dynamic Data
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Solution Overview
Problem
Conventional graph databases are optimized either for querying or writing data, leading to inefficiencies in handling fast-changing, highly dynamic data, particularly in applications like sensor networks where data frequency is high.
Innovation Solution
A graph database management system that stores data in the form of RDF triples with associated memory addresses, allowing for fast updates and management of dynamic data without modifying the storage or querying process, using a cache and main memory architecture and a look-up table to optimize both data writing and querying performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the graph database is optimized for data querying, then data reading performance is improved, but data writing becomes slow
Solution Approach 1:
The patent segments the storage system into two distinct components: a cache memory for high-speed data writing and a main memory for data querying. This segmentation allows each component to be optimized for its specific function, resolving the contradiction between fast writing and fast querying.
Solution Approach 2:
The cache memory acts as an intermediary between the data writing process and the main memory. It temporarily stores incoming data at high speed, then transfers it to main memory in optimized batches, thereby decoupling the writing speed from the querying performance.
2Productivity
If the graph database is optimized for data writing, then data writing speed is improved, but data querying becomes slow
Solution Approach 1:
By dividing the memory system into cache and main memory components, the patent enables the main memory to be optimized for querying operations while the cache handles writing operations, thus resolving the speed trade-off.
Solution Approach 2:
The patent creates a copy of the data storage function by introducing cache memory as a separate layer. This copy allows data to be written at high speed to the cache while maintaining the original main memory structure optimized for querying.
3Adaptability or versatility
If the graph database stores highly dynamic data, then data dynamism handling is improved, but memory overhead increases
Solution Approach 1:
The patent extracts the memory address information from the main data storage and places it in a separate look-up table. This extraction reduces the memory overhead in the main storage while maintaining fast access to dynamic data through the look-up table.
Solution Approach 2:
The look-up table acts as an intermediary that stores only the essential memory address mappings. This intermediary structure reduces the overall memory overhead by separating the address storage from the data storage, while still enabling fast access to highly dynamic data.
Data Source
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AI summary
Various example embodiments of the present disclosure relate to a graph database management system comprising at least one processor and at least one memory including computer program code, the at least one memory and computer program code configured, with the at least one processor, to perform storing, in the memory, data in the form of data records in accordance with an entity-relationship model, the data records comprising at least a subject, a predicate, and an object, the database management system being further configured to perform: deriving memory addresses of respective objects stored in the memory; associating the memory addresses with the respective objects; and storing, in the memory, the memory addresses associated with the respective objects. Further example embodiments related to a method for manipulating data in a graph database management system, a computer program product, and a computer readable storage medium.