Non-indexed In-memory Trading Data Storage for Real-time Query Speed
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Solution Overview
Problem
Conventional databases face inefficiencies in processing and retrieving large volumes of trading data in real-time, leading to delayed query results and inability to analyze data quickly, due to the use of indexes that are not adaptable to changing user needs or data perspectives.
Innovation Solution
Storing trading data in a non-indexed, sequential manner on computer-readable media, such as solid-state memory, allowing for rapid queries without the speed limitations and overhead associated with indexed databases, and enabling real-time data analysis by physically arranging records in the order of query performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional databases use indexes to speed up data retrieval, then query speed is improved, but the system becomes unable to handle changing user needs or data perspectives rapidly
Solution Approach 1:
The patent applies dynamics by making the data organization structure adaptable to changing query patterns. Instead of static indexes, the system dynamically reorganizes data in memory based on actual query sequences, allowing the storage structure to evolve and adapt to new user needs and data perspectives in real-time.
Solution Approach 2:
The patent changes the parameter of data organization from fixed indexed structures to flexible sequential arrangements. By altering how data is physically stored and accessed in memory, the system can rapidly adapt to different query requirements without being constrained by predetermined index structures.
2Loss of time
If precomputed summary data is used to reduce response time, then retrieval speed is improved, but the system requires users to specify data in advance and cannot rapidly adapt to new perspectives
Solution Approach 1:
The patent applies preliminary action by pre-positioning data in memory sequences that anticipate likely query patterns, while maintaining the flexibility to reorganize based on actual queries. This allows rapid access without requiring users to pre-specify all their data needs in advance.
3Quantity of substance
If conventional databases process large volumes of trading data, then data storage capacity is improved, but query results are delayed due to substantial chip clock cycles
Solution Approach 1:
The patent transitions from traditional disk-based storage to in-memory storage, adding the dimension of memory speed to the data access equation. This dimensional change allows the system to maintain large data capacities while achieving rapid query processing by eliminating mechanical access limitations.
4Use of energy by moving object
If batch mode processing is used to aggregate trading data, then computing resource consumption is reduced, but real-time analysis capability is lost
Solution Approach 1:
The patent enables continuous real-time data aggregation and analysis by maintaining data in memory where it can be continuously processed without batch interruptions. This allows the system to perform useful computational actions continuously on incoming trading data, delivering real-time insights while managing resources efficiently through the speed of in-memory operations.
Data Source
AI summary
Systems, methods and user interfaces that allow rapid storage and retrieval of trading data are provided. Trading data records are arranged as a non-indexed collection of data records. The physical location of trading data records stored in a computer-readable medium corresponds to the order that queries are performed. Queries may be performed by analyzing attributes of all of the trading data records, without speed limitations associated with indexed databases.