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Data Vault (hubs, links, satellites)

Integrating many changing sources into a warehouse without constant rework.

Reference architecture canvas Sources feed processing stages; a data contract sits between processing and destinations; a failure path routes invalid output to a dead-letter zone. OLTP DBs cdc Event log stream Processing transform · model idempotent writes versioned code Data contract schema · grain · SLA validated at boundary Warehouse analytics Feature/API agents · apps Dead letter quarantined output

At a glance

What Integrating many changing sources into a warehouse without constant rework.
When Enterprise integration of many sources; Strong audit/lineage requirements
Where Data Warehouses

Problem

Integrating many changing sources into a warehouse without constant rework.

Solution

Model the raw integration layer as insert-only: hubs — business keys links — relationships between hubs satellites — descriptive attributes over time Loads are insert-only and parallel, so a source change adds a satellite rather than forcing a rewrite. Build star schemas as a downstream, disposable layer.

When not to use

  • A single source feeding a known set of reports

Security scan

Last sweep 2026-10-24: 0 finding(s), 0 marked as examples.

Context

Many source systems, frequent schema changes, auditability requirements.

Forces

  • Sources change constantly
  • History and auditability are mandatory
  • Loads must be parallel and restartable

Tradeoffs

Choose this when Costs & caveats
resilient to change, auditable, parallel loads more objects, harder to query directly; needs a downstream marts layer

Diagram

source ─▶ hub_customer ─┐
         hub_order    ─┼─ link_order_customer ─▶ sat_* ─▶ star marts
source ─▶ hub_product ──┘

Registry stats

Verification community · Sep 14, 2026
Completeness 75
Trust multiplier ×1.25
Composite 34.75 · adequate
Freshness 40 days since last source check
Difficulty advanced
Version 0.9.0
License CC-BY-4.0
Security flags none