Identify the payload or state that must survive beyond the current processing attempt.
Integration Styles
Shared Database
Let applications coordinate through a common data store. This can simplify consistency but also couples participants to a shared schema, ownership model and release process.
How can I integrate multiple applications so that they work together and can exchange information?Adapted from Enterprise Integration Patterns under CC BY 3.0. The visualization and explanatory content on this page are original GateSift material.
Original GateSift visualization
How Shared Database works
The integration persists data or processing state so it can be recovered, deduplicated or retrieved later.
Message or payload
Shared Database
Durable reference / state
Apply Shared Database to persist, reference or verify that state.
Retrieve or reuse the stored information when the flow continues or recovers.
What this pattern helps you decide
Let applications coordinate through a common data store. This can simplify consistency but also couples participants to a shared schema, ownership model and release process.
What happens when processing fails or the same message is delivered twice?
Where does state, correlation or routing configuration live?
How will operators trace the message and understand the decision path?
Where you may see it
- Azure SQL shared integration tables
- Cosmos DB integration state
- Staging schemas used by ETL
How the analyzers can surface it
- SQL and WCF-SQL endpoints
- Shared connection or schema dependencies
Pattern detection is contextual. GateSift should present these as architectural signals, not claim a pattern is implemented solely because one policy statement or adapter exists.
Source, licence and attribution
The pattern name and selected problem statement are adapted from Enterprise Integration Patterns by Gregor Hohpe and Bobby Woolf under CC BY 3.0. GateSift summaries, Azure mappings, analyzer guidance and diagrams are original. No endorsement by the original authors is implied.