Materialized View Platform Data Stream History
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Solution Overview
Problem
The increasing complexity and cost of managing and integrating data from multiple disparate data storage systems, particularly in scenarios requiring near real-time updates, are challenges due to the need for custom code and complex integration workflows, which can decrease system performance and increase implementation costs.
Innovation Solution
A materialized view management platform that simplifies the creation and maintenance of integrated views from multiple data sources, providing a serverless experience for automatic scaling and near real-time updates, without requiring custom infrastructure setup or configuration, by using a materialized view management platform that creates and updates views in a target data store while maintaining data stream history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is distributed across multiple disparate storage systems to optimize performance and analysis benefits, then data storage efficiency is improved, but system complexity and integration difficulty increase
Solution Approach 1:
The patent introduces a materialized view management platform as an intermediary layer between disparate data storage systems and applications. This platform automatically creates and maintains materialized views that consolidate data from multiple sources, eliminating the need for applications to directly integrate multiple storage systems. The platform handles data retrieval, transformation, and presentation transparently, reducing integration complexity while preserving the benefits of distributed storage.
Solution Approach 2:
The materialized view management platform provides universal access to data from multiple disparate storage systems through a single unified interface. It supports various data sources (relational databases, NoSQL databases, data lakes, cloud storage) and provides consistent data access patterns, making the system adaptable to different storage technologies without requiring application-specific integration code for each source.
2Adaptability or versatility
If custom integration workflows are implemented to access data from multiple storage systems, then data accessibility is improved, but implementation cost and time increase
Solution Approach 1:
The system performs preliminary actions by automatically creating and maintaining materialized views in advance. When data is needed, the materialized view is already prepared and available, eliminating the need for runtime data gathering from multiple sources. The platform pre-computes and stores aggregated results, so applications can access integrated data immediately without implementing custom integration workflows.
Solution Approach 2:
The materialized view management platform is self-service in that it automatically discovers data sources, creates appropriate materialized views, and maintains them as source data changes. The system self-adjusts to data schema changes and automatically updates materialized views without requiring manual intervention or custom integration code, significantly reducing implementation and maintenance time.
3Speed
If data is co-located for systems needing access to multiple data sets, then system performance is improved, but data removal from optimized source locations increases complexity
Solution Approach 1:
The system creates copies of data in materialized views rather than moving or removing data from source storage locations. The materialized view management platform replicates necessary data subsets into optimized formats for analytical queries, allowing fast access without affecting the original storage systems. This copying approach maintains data at optimized source locations while providing co-located access points for performance-critical operations.
Solution Approach 2:
The system segments data into appropriate formats and locations based on access patterns. Hot data that requires frequent analytical access is segmented into materialized views with optimized structures, while source systems retain complete data in their optimized formats. This segmentation allows different portions of data to reside in different locations optimized for their specific access requirements, improving overall system performance without complex data movement.
4Adaptability or versatility
If manual data integration workflows are used to combine data from disparate sources, then data integration capability is improved, but operational overhead and maintenance cost increase
Solution Approach 1:
The materialized view management platform implements continuous feedback loops that monitor source data changes and automatically trigger materialized view updates. When source tables are modified, the platform detects these changes and refreshes corresponding materialized views, ensuring data consistency without manual intervention. This automated feedback mechanism eliminates operational overhead associated with manual data synchronization while maintaining versatile integration capability across multiple data sources.
Data Source
AI summary
Materialized views may be generated at a managed materialized view platform that accepts data streams as a source. When updating a materialized view with a data stream as a source, a stored portion of the stream is used to maintain a history of changes to be made. When a join operation needs to utilize the data stream source to determine an update to the materialized view, the data stream is preserved to complete the join and update the materialized view.