Microsoft and Google are supporting Apache Ossie, an open specification that lets enterprises move semantic models between analytics platforms without rebuilding them. The backing from major vendors makes portability more likely, but governance gaps and the spec's early stage mean enterprises still face real constraints in switching platforms.

• Microsoft is building two-way converters between Power BI and Ossie, and pushing for DAX language support, so calculation logic moves with models across platforms instead of needing recreation.
• Governance features like row-level security and access policies aren't included in the current spec, forcing enterprises to reconfigure these on each platform even with portable models.
• Ossie uses a hub-and-spoke model where the spec acts as a common format and individual vendors provide converters, reducing engineering overhead compared to point-to-point translations.
• The specification is still in development (version 0.2), lacks capabilities large enterprises need like cross-model references, and won't eliminate vendor lock-in—just shift it to platform-specific execution behavior.

Apache Ossie is an Apache Incubator project that defines a vendor-neutral YAML spec for semantic data models. It lets teams declare metrics, dimensions and joins once and share them across BI, analytics and AI tools. This prevents metric drift, cuts integration debt and creates a single source of truth.

• Apache Ossie standardizes metric/dimension definitions in YAML so BI, analytics, and AI tools all reference one shared source of truth instead of redefining metrics per dashboard.
• Over 50 organizations, including Snowflake, Databricks, Oracle, Salesforce, dbt Labs, Qlik, and ThoughtSpot, have joined the effort.
• The spec was renamed from Open Semantic Interchange to Apache Ossie in July 2026, shortly after launching a Financial Services Semantic Working Group in June 2026.
• It embeds AI context instructions so LLMs can ground answers in official business logic, aiming to cut reconciliation costs and eliminate conflicting dashboards.