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Use an insert-only event ledger as the record of what your game-rewards platform decided and did—not as proof that a user completed an offer or as a guarantee that a payout reached them. Keep ordinary application roles from changing past entries, record the evidence and actor behind each state change, and reconcile reward decisions with offer terms, completion signals, payout attempts, and support cases.

What an insert-only ledger does—and does not—prove

A ledger records a sequence of events. Instead of overwriting a row when a reward moves from pending to approved, the system appends a new event that refers to the earlier decision. That gives engineers, support staff, and auditors a history to inspect.

“Insert-only” is a permission model for ordinary application roles, not absolute immutability. PostgreSQL separates the privileges to insert, update, delete, and truncate rows, while an object’s owner retains stronger powers. An owner or sufficiently privileged administrator may be able to change grants, alter the schema, disable a trigger, or otherwise modify the controls. Describe the result accurately: the design can make routine application writes append-only and make exceptions easier to detect when separate controls are in place. It is not, by itself, tamper-proof or cryptographically immutable.

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Nor does a database entry establish that an offer was completed correctly. The ledger can show that the platform accepted a completion signal and issued a reward decision. Whether that signal was valid depends on the offer rules, attribution evidence, validation process, and any later investigation.

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Model rewards as events, not a mutable balance

A displayed balance is convenient for users, but it should be a projection of the event history or a cache derived from it—not the only record of what happened. If the projection is wrong, a team should be able to rebuild it from the events and reconcile the result.

Fields that make an event explainable

An illustrative ledger entry might contain:

ledger_entries: id, account_id, event_type, amount_minor, currency, source_event_id, idempotency_key, offer_id, offer_version, actor_type, actor_id, occurred_at, recorded_at, reason_code, metadata

This is a design example, not a Supabase- or PostgreSQL-prescribed schema. The fields serve distinct questions: which account and offer were involved, which version of the offer applied, what event was recorded, who or what recorded it, when it occurred and was stored, and what earlier event or external signal it relates to. Store monetary values in minor units with an explicit currency rather than relying on ambiguous decimal formatting.

Keep payout attempts and their status history separately identifiable. Include the payout provider’s reference and reconciliation timestamps so a queued payout, a failed attempt, and a confirmed delivery are not collapsed into one “paid” flag.

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Represent transitions and corrections explicitly

A reward might progress through reported → pending validation → approved → payout queued → paid, with branches such as held, rejected, or reversed. For each transition, record the actor, time, reason, and relevant evidence reference. These labels are an example; choose and document states that match the actual product and payout process.

If an earlier decision was wrong, append a reversal or adjustment that points to the original entry and explains why. Do not silently rewrite or delete the original earning event. Give callbacks a stable idempotency key and enforce uniqueness for it so a retry does not award the same completion twice. Define how the system handles out-of-order callbacks rather than assuming they always arrive in sequence.

Restrict writes by role, ownership, and access path

Supabase is a hosted Postgres platform, but the project team remains responsible for its schema, access levels, application architecture, security controls, and secrets. Supabase recommends row-level security (RLS); its shared-responsibility guidance makes clear that a hosted database does not transfer those responsibilities to the provider.

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  1. Separate the table owner from application roles. Use a narrowly controlled owner and migration path. Avoid running routine application traffic with ownership or administrator privileges.
  2. Grant ordinary application roles only the operations they need. In particular, do not give them UPDATE, DELETE, or TRUNCATE on the ledger if the intended policy is append-only.
  3. Put trusted writes behind a server-side authorization boundary. A client must not be able to assert its own earned balance or submit an unrestricted privileged write. Protect service credentials and never expose a privileged secret in a user-facing client.
  4. Apply RLS to reads and any permitted row-level operations. Check that a user can access only the rows the product intends to expose. RLS is not a substitute for backend authorization or careful privileged-function design.
  5. Audit privileged paths. Track who can change grants, schema, triggers, secrets, and migration code, and use those powers sparingly.

A database function can be part of a trusted write path, but a function that runs with elevated privileges must be designed carefully. Verify its authorization checks and exposure; do not treat the existence of a function or RLS policy as proof that the path is safe.

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Use triggers as guardrails, not as the trust boundary

PostgreSQL triggers can reject selected row changes, and event triggers can guard against selected DDL actions. Supabase documents an event-trigger example that prevents a table from being dropped, along with the privileged scope and override path. Such controls can make accidental changes harder, but sufficiently privileged operators can reconfigure or bypass them.

Permissions and ownership should therefore carry the main policy for ordinary application traffic. Triggers can add defense in depth—for example, rejecting updates or deletes from application paths—but they do not make the table universally immutable. If an administrator-level change must be detectable, use a separate audit or monitoring control rather than relying only on a trigger in the same database.

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Reconcile the offer, completion, ledger, and payout

An auditable event history is most useful when each reward can be traced across the systems that made it possible. For each disputed or sampled reward, compare four records:

  1. Offer terms: the offer identifier and the exact version shown to the user, including qualifying actions, reward amount, and any stated delivery window.
  2. Completion evidence: the attribution or other completion signal received, with its external reference and validation outcome.
  3. Ledger decision: the accepted or rejected event, the reason code, the actor, and any link to the evidence.
  4. Payout outcome: the queued attempt, provider reference, status changes, and result or reconciliation time.

Track mismatches as unresolved work, not as an unexplained balance difference. For example, a completion signal without an accepted ledger event needs an investigation path; an approved reward without a matching payout result needs a payout follow-up. Give users a support route that can identify the offer and explain whether a reward is pending, held, rejected, reversed, or paid.

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The FTC’s 2020 proceeding concerning Tapjoy is a case-specific example of why offer disclosures, delivery validation, accessible support, and review of complaint or conversion patterns matter operationally. It is not a universal database schema or legal checklist. The broader engineering lesson is to preserve what the user was told and what the platform did, so a dispute can be investigated against the relevant terms and evidence.

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Make reward states and consumer expectations clear

A number shown in an app is not necessarily money already paid or irrevocably owed. Explain each status in plain language and distinguish approval from payout delivery. If a reward is held or rejected, show a meaningful reason where appropriate and provide a route to ask for help. If delivery is expected within a stated period, communicate that period rather than implying immediate payment.

The FTC’s 2024 consumer guidance warns: “Never pay anyone to get paid, or to get a job.” A platform’s support and payment flow should not ask users to pay a fee to release an earned reward.

Backups support recovery, not reward validation

A backup can help restore database state after loss or corruption; it cannot establish that a reward event was valid or explain why the application accepted it. Supabase’s backup capabilities and retention depend on the project’s plan and database setup, and restore operations may make a project unavailable while they run. Storage API objects are not included in database backups.

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Before promising a recovery point, check the current backup options for the project’s plan and database version, the configured retention or point-in-time recovery window, and the operational requirements for a restore. Set recovery objectives, test the restore procedure, and consider independent copies for the records and evidence your dispute process depends on. Do not assume that enabling backups guarantees zero data loss or uninterrupted service.

Review the design before launch

  • Can ordinary application roles insert events but not update, delete, or truncate ledger history?
  • Are the owner, migration, service, and user-facing roles separate and access-controlled?
  • Can each reward event be tied to a specific offer version and completion reference?
  • Do retries and out-of-order callbacks have defined, testable behavior?
  • Are corrections represented by linked reversal or adjustment events?
  • Can users see an understandable status and reach support about a missing or delayed reward?
  • Can the team reconcile ledger decisions against payout-provider results and investigate mismatches?
  • Have recovery objectives, backup scope, retention, and restore downtime been verified for this project?

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