Cloud DBs are caches, not sources

Firestore, Turso, R2 are caches rebuilt from canonical JSONL git store on every deploy. If any of them dies, the next deploy reconstructs it from JSONL.

Cloud DBs are caches, not sources

Concept

Firestore (user state), Turso (warm-cache lifestream events), and R2 (media uploads, when needed) are all treated as caches over the git canonical. Their job is to make queries fast at the edge. Their job is NOT to be the source of truth. Any one of them can be dropped and rebuilt from git clone + the rebuild script.

How it works

• Turso warm-cache: the GitHub Actions cron parses oriz-me-data JSONL, normalises into the events SQL schema, and writes via the @tursodatabase/serverless write client
• Firestore: holds account-shaped data that is itself canonical there (subscription state, preferences) — but those documents are derived from external systems (Razorpay webhook for subscription, client UI for preferences) which are themselves replayable
• R2: media uploads are addressed by content hash; the canonical index of “which hash is what” can live alongside the JSONL
• The rule: if any cache vanishes, the next CI run rebuilds it from the canonical without manual intervention

Why this shape

A hosted DB as canonical is a single-point-of-failure with no migration story. A git-canonical with hosted-DB caches inverts that: the canonical is mirrorable everywhere, and the caches are disposable. The cost is one rebuild-cache.ts script per cache — paid once, runs on every deploy.

This also makes free-tier limits less stressful. If Firestore reads spike one day, the cache can absorb it via Turso. If Turso is saturated, the build-time JSON bake is always there. There is always another tier underneath because git is at the bottom.

Cross-refs

• The canonical store these caches mirror → canonical-store-jsonl.md
• The SQL shape Turso holds → events-table-schema.md
• The full data-shape sharding picture → layer-4-database-by-shape.md
• What runs the rebuild scripts → layer-5-compute.md

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