Event Sourcing Model

• Events are immutable facts appended in order; they are the single source of truth and anchor Merkle proofs.
• Aggregates group related events, enforce identifiers and schemas, and expose the current state derived from the full event stream.
• Snapshots cache that derived state at specific versions so reads and plugins stay fast without replaying the entire history.
• Replays rebuild snapshots from events; snapshots prove what state existed at a version; aggregates tie both to a consistent identity.
• Derived aggregate state can also serve reads/plugins directly when you don’t need a cached snapshot.

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Snapshots

• Materialize deterministic snapshots to serve reads quickly without replaying full histories.
• Schedule rebuilds or let EventDBX auto-refresh them once schema thresholds are reached; add dbx snapshots create for point-in-time checkpoints before migrations or audits.
• Tune retention, compression, and pruning strategies to balance cost versus recovery speed; pair exports with Merkle roots to prove integrity.

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Aggregates

• Keep identifiers stable, scoped, and easy to shard across teams.
• Use metadata to track lifecycle decisions, ownership, and reconciliation markers.
• Avoid coupling unrelated concerns into a single aggregate—fan out instead; use domains to hard-wall environments and tenants via dbx checkout.

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Events

• Version payload schemas carefully so older events remain readable.
• Lean on metadata for traceability, idempotency, and auditing hooks; extensions-only payload mode lets plugins consume hints without payloads.
• Rebuild downstream read models by plugin-replaying events (dbx plugin replay … --payload-mode <mode>) whenever integrations drift; queue backoff keeps writes decoupled from slow consumers.