Cloud Market Data Grid Bus for Elastic Streaming Integration
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Solution Overview
Problem
Current market data platforms are inefficient and costly to modernize due to their reliance on proprietary hardware and lack of elastic scalability, making it difficult to integrate and manage large volumes of streaming data from multiple sources while maintaining compatibility with legacy systems.
Innovation Solution
A cloud-based market data utility system that includes a data ingress normalizer, a global elastic grid bus, and snapping interfaces to normalize and distribute data across a single namespace, supporting elastic scaling and integration with both on-premises and cloud-native applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current market data platforms use proprietary hardware and dedicated server hardware, then system reliability is maintained, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses virtualization to create virtual copies of computing resources instead of relying on physical proprietary hardware. Virtual machines and containers provide the necessary system reliability while eliminating the need for dedicated physical servers, thereby reducing device complexity and hardware costs.
Solution Approach 2:
The patent replaces mechanical/physical hardware systems with software-based virtualized infrastructure. By substituting physical servers with virtualized computing environments, the system maintains reliability through software abstraction while significantly reducing hardware complexity and associated costs.
2Quantity of substance
If market data platforms process large volumes of streaming data from multiple sources, then data completeness is improved, but processing speed and efficiency deteriorate
Solution Approach 1:
The patent segments the data processing workflow into distinct modular components including data ingestion services, normalization services, and distribution services. This segmentation allows each component to process data independently and efficiently, maintaining high processing speeds while handling large volumes of streaming data from multiple sources.
Solution Approach 2:
The patent implements dynamic, elastic processing capabilities that can scale up or down based on data volume demands. The virtualized infrastructure allows processing resources to be dynamically allocated and adjusted in real-time, ensuring high processing speed whether handling small or large data volumes.
3Adaptability or versatility
If physical appliances are removed from data centers to modernize, then adaptability to cloud infrastructure is improved, but hundreds of virtual machines are required increasing cost and time
Solution Approach 1:
The patent creates a universal virtualized platform that can serve multiple functions and support various cloud infrastructure requirements. This multi-functional approach consolidates what would otherwise require hundreds of separate virtual machines into a more efficient unified system, reducing both cost and modernization time while maintaining cloud adaptability.
4Adaptability or versatility
If data is normalized and distributed across a single namespace, then data integration is improved, but system complexity increases
Solution Approach 1:
The patent introduces a data normalization service as an intermediary layer between data sources and distribution channels. This mediator handles the complexity of normalizing diverse data formats into a unified namespace, improving data integration while shielding other system components from the underlying complexity through abstraction.
Data Source
AI summary
An embodiment of the present invention is directed to a full re-write of an entire data stack in a cloud-native manner. With an embodiment of the present invention, a reference data store that may be merged with a subsystem that normalizes inbound streaming data sets from in-cloud sources to feed a Global Elastic Grid Bus. The Global Elastic Grid Bus may be responsible for caching and distributing the information globally, as well as maintaining a single namespace accessible to some or all customers.