Platform Integrations

Makoto is a specification — the same DBOM format works on any pipeline platform. These pages explore how Makoto attestations could be emitted natively from common data tools. All integrations are conceptual: real 9-platform coverage is the goal, not the current state.

Status: All integrations on this page are integration concepts. They use real platform APIs and patterns, but Makoto-specific pieces (operators, hooks, processors, decorators) are sketches. If you want to ship one for real, open an issue.

Supported Platforms

Common Integration Patterns

Most platforms expose at least one of these surfaces — Makoto plugs into whichever is most natural:

Pattern Where Makoto attaches Used by
Lifecycle hook on_success / on_completion callbacks fire after each task Airflow, Prefect, Dagster
Custom operator/asset Drop-in subclass that wraps existing primitives Airflow, Dagster, Databricks
Interceptor / SMT Per-message hook on producer/consumer or connector Kafka, Kafka Connect
Macro / post-hook SQL-templating language injects attestation into transforms dbt, Snowflake
Listener / event subscriber Catalog or platform fires events on materialization Spark, Databricks, Unity Catalog
IO manager / result serializer Hash on write, verify on read Dagster, Prefect

Bring Your Own Platform

Don't see your platform? The Makoto spec is platform-agnostic by design. The pattern table above covers most cases — if your pipeline can produce a content digest and sign a DSSE envelope, it can ship a DBOM.

Read the Spec View the SDKs Request a Platform