Transaction Processing Balance Cache Analytics
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Solution Overview
Problem
Conventional computer systems experience high latency and resource utilization when processing transactions that involve asset transfers between accounts, as they require locking database portions, leading to inefficiencies in analytics and processing.
Innovation Solution
Implementing a distributed computer system that uses a balance cache to update account balances in real-time without accessing the database, allowing transactions to be processed without locking database entries, and utilizing an incentive ID cache for efficient analytics and behavior scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If database queries are used to perform analytics on transaction data, then analytics can be performed, but processing resources are heavily consumed and latency increases beyond acceptable thresholds
Solution Approach 1:
The system pre-computes and stores analytics data in advance in a data mart structure, so that when analytics queries are executed, the data is already prepared and readily available, eliminating the need for computationally intensive real-time database queries
Solution Approach 2:
A copy of the transaction data is created and stored in a specialized analytics-optimized structure (data mart) that is separate from the operational database, allowing analytics to be performed on the copy without impacting the original database performance or resource utilization
2Reliability
If database locking is implemented to ensure data consistency during transactions, then data integrity is maintained, but latency increases beyond acceptable thresholds especially for multiple transactions affecting the same account
Solution Approach 1:
The database is segmented into a operational database and a separate data mart structure, allowing transactions to be processed in the operational database without locking the entire system, while analytics operate independently on the data mart copy
Solution Approach 2:
An intermediary data mart layer is introduced between the operational database and analytics queries, acting as a buffer that allows analytics to access data without requiring locks on the operational database, thus maintaining data consistency while reducing latency
Data Source
AI summary
Certain embodiments described herein enable real or near-real time monitoring and updating of analytics associated with transactions performed by a computer system that cause assets to be transferred between accounts of different entities, without necessitating that a query be run against a database that stores transaction data for the transactions performed by the computer system. Other embodiments described herein enable updating of balances in each of a plurality of different accounts without needing to access a database within which data for each of a plurality of processed transactions is stored, and without needing to lock a database, or portion thereof. Still other embodiments overcome other deficiencies of computer systems that are used for processing transactions and providing analytics and feedback relating to the transactions.


