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Sekiban DCB’s documented materialized-view implementation uses PostgreSQL and is delivered separately from the main event-store package. The feature is split across core, PostgreSQL, and Orleans packages, each with a distinct role. The available documentation establishes this architecture, but not a complete runnable setup; check the current Materialized View Basics guide and package versions before using specific APIs or code.
How a Sekiban DCB materialized view works
A materialized view is a read model derived from events: select the events relevant to a projection, then apply event handlers to fold them into state. In DCB guidance, a projection is described through its initial state, handlers, and a query or tag filter. Small projections can be composed, and a helper library is optional. The query should be translated into a form the event store can execute.
This projection model is general DCB guidance, not a Sekiban-specific setup recipe. The DCB specification describes a query as OR-combined items; within each item, event types match one of the listed types, and the event must carry every listed tag. Stores must read sequenced events matching a query and atomically persist events. An optional append condition can enforce consistency. See the DCB projections guidance and DCB specification.
Which Sekiban packages are involved?
Sekiban documents the materialized-view feature as separate from its main event-store package. The three materialized-view packages cover different responsibilities:
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| Package | Documented responsibility |
|---|---|
Sekiban.Dcb.MaterializedView |
Core contracts and a hosted catch-up worker |
Sekiban.Dcb.MaterializedView.Postgres |
Registry, executor, row access, and table updates |
Sekiban.Dcb.MaterializedView.Orleans |
Grain orchestration and a query accessor |
These roles are documented in Sekiban’s storage providers guide. They describe the architecture, not the exact dependency set or registration sequence for every application. Confirm the current guide and compatible package versions for your target project before selecting packages or writing setup code.
Can the read model use a different database?
Sekiban’s documented proof of concept allows events to remain in one database while materialized-view tables are stored in a separate PostgreSQL database or schema. This gives the event store and read model an operational boundary: they can be separated, but the documented materialized-view table implementation remains PostgreSQL-based.
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Sekiban lists PostgreSQL, Cosmos DB, and DynamoDB among event-store choices, but that does not establish materialized-view table support for all three. The repository recommends Sekiban DCB for new projects; treat event-store selection and view-storage support as separate decisions. The Sekiban repository and its storage guide are the relevant references.
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The architecture points to a sensible implementation sequence, but current detailed setup instructions are necessary before turning it into executable code:
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- Define the read shape. Identify the queries the view must serve and the event types and tags that determine which events feed its state.
- Specify projection behavior. Define the initial state and event handlers, and decide whether the projection is small enough to compose or benefits from a helper library.
- Choose the storage boundary. Decide whether view tables belong in the event-store database, a separate PostgreSQL database, or a separate schema. The documented separation example still uses PostgreSQL for view tables.
- Map package roles to the application. Use the package responsibilities above as an architectural guide, then confirm current dependency and registration instructions in the storage providers guide and its linked Materialized View Basics page.
- Validate operational requirements. Decide how much catch-up delay is acceptable and how the separate database or schema will be operated. No performance figures or measured delay guarantees are established by the cited documentation.
The detailed basics page contents, exact registration APIs, schema and migration steps, concurrency behavior, runnable sample, and performance characteristics are not established here. Do not infer them from package names or generic DCB projection guidance; verify them against the current Sekiban documentation and package versions before adopting code.
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Assess the design against the actual read model and operational requirements, rather than assuming a materialized view is automatically faster or simpler:
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- Query shape: Does a projection built from matching event types and tags serve the reads the application needs?
- Freshness: Is the catch-up delay acceptable for those reads?
- Operations: Is it useful to separate event storage from PostgreSQL view tables by database or schema?
- Storage constraint: Does PostgreSQL meet the materialized-view storage requirement, even if the event store uses another supported option?
No comparative benchmarks or scale measurements are established, so these are design questions—not evidence of a performance advantage.
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