Extensible Persistence Hierarchies for Workflow Management
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Solution Overview
Problem
Workflow management systems face inefficiencies in accessing and managing external operational data, as existing methods require manual intervention and the use of cumbersome proxy layers, leading to performance issues and increased developer burden.
Innovation Solution
Implementing a data access language component that allows seamless, declarative access to external data stores, transparently copying and processing operational data in a short-lived session, and automatically updating the external data store, thereby reducing the need for manual handling and optimizing data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If all application state and business data are stored within the workflow context structure, then any type of data can be stored generically, but data storage becomes expensive and performance deteriorates
Solution Approach 1:
The patent segments data storage into two distinct layers: workflow context structure for application state information and external data stores for operational data. This segmentation allows each layer to be optimized independently - the context structure maintains versatility for workflow control data while external stores handle operational data efficiently, resolving the contradiction between storage flexibility and execution performance.
Solution Approach 2:
The patent extracts operational data from the workflow context structure and stores it in external data stores. This extraction removes the performance burden from the context structure while maintaining the ability to access operational data when needed, thereby improving workflow execution performance without sacrificing data storage versatility.
2Adaptability or versatility
If a generic persistence approach is used in the workflow context structure, then any type of data can be stored, but it is not optimized for any particular type of information
Solution Approach 1:
The patent introduces external data stores as intermediaries between the workflow context structure and operational data. These intermediaries are specifically optimized for particular types of operational data while the context structure remains generic for application state. This intermediary layer maintains data type compatibility through standardized interfaces while providing optimized storage and access for specific data types.
3Ease of operation
If operational data is stored in the workflow context, then data is readily accessible during workflow execution, but versioning and snapshot requirements increase storage costs
Solution Approach 1:
The patent extracts operational data from the workflow context structure to external data stores, eliminating the need to maintain copies in the context. This extraction reduces storage costs associated with versioning and snapshots while maintaining data accessibility through efficient external store interfaces and selective data copying only when absolutely necessary for workflow execution.
4Ease of operation
If manual intervention and proxy layers are used to access external data stores, then data can be accessed, but developer burden increases and performance issues occur
Solution Approach 1:
The patent implements self-service mechanisms where the workflow management system automatically manages data access between the context structure and external data stores. The system handles data copying, persistence, and retrieval automatically without requiring manual proxy layer implementation by developers. This automation reduces both developer burden and system complexity while maintaining efficient data access capabilities.
Data Source
AI summary
Methods and systems may be associated with a workflow management environment. An external data store may be associated with a persistence technology to contain operational data. A workflow management platform may include a running workflow and a workflow context associated with a persistence technology to contain application state information. A data access language component may be coupled between the running workflow and the external data store to access the operational data in a declarative way. The data access language component may, for example, copy the operational data transparently for a developer of the running workflow. The data access language component may then store the operational data transiently in a short-lived session and, after the operational data is processed by the running flow, release the operational data. According to some embodiments, changes made to the to the operational data are automatically played back to the external data store.