Microsoft and Google back Apache Ossie's shared format for moving semantic models between platforms
Microsoft and Google are joining Apache Ossie, an open format for moving semantic models between platforms that more than 60 companies already back. Its shared hub cuts converter work, though analysts say lock-in eases only as far as the format can carry each vendor's logic.
The Scientist · Science desk
What happened
- The project began as Open Semantic Interchange and became Apache Ossie when the Apache Incubator accepted it in June.
- Ossie describes semantic models, including datasets, fields, relationships, metrics and AI context, in JSON and YAML.
- Microsoft is building a two-way converter between Power BI semantic models and Ossie, the company wrote in a blog post.
- Microsoft also wants the spec to support more of its ontologies and to recognize DAX, the Power BI language for calculations and business metrics.
- Google is still in the process of joining, a representative said by email, and has not detailed what it plans to contribute.
Why it matters
- What it costs cost Teams that move analytics workloads between platforms would spend less effort rebuilding the same semantic definitions each time, according to Aditya Ranjan, a senior data engineer at H-E-B.
- Who has to decide decision Buyers weighing a switch of BI or data platform gain leverage if the move no longer means rebuilding the semantic layer from scratch, HyperFrame Research's Stephanie Walter said.
- What's now possible capability Developers building AI agents could give every agent the same metric definition across platforms, so two agents are less likely to read one metric differently, Walter said.
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Ossie is built as a hub. Each vendor needs one converter to and from the common format, so no pair of platforms needs its own translator [11]. InfoWorld names five platforms the format is meant to work across: Snowflake, Databricks, Tableau, ThoughtSpot and Sigma [10]. Linking those five pair by pair would take 10 two-way converters. Through the hub it takes five [18]. Add Power BI and the counts become 15 and six [19].
The thing the converter count doesn't tell you is how much of a model arrives intact. In a hub design, a model moving between two vendors goes through two conversions, out to Ossie and back in on the far side [20]. Stephanie Walter, practice leader of AI stack at HyperFrame Research, said portability does not necessarily mean complete interoperability [8]. How far a model can move, she said, depends on how much vendor-specific logic Ossie can represent and how accurately the destination platform can interpret it [8].
Microsoft's push to have DAX recognized goes at the first of those limits. The company wrote that enterprises could then carry the calculation logic that gives a semantic model its business meaning along with the model itself [4]. Walter's second limit still applies. A destination platform would have to interpret those calculations accurately [8]. Google's dialect is already there: the specification lists BigQuery/GoogleSQL as supported, a result of "early community contributions that recognize BigQuery's footprint across enterprise data stacks," a Google representative said [6].
The benefits analysts describe rest on the same coverage question. Ashish Chaturvedi, executive research leader at HFS Research, said recreating and maintaining the same business definitions across platforms often leads to metric drift [14]. With Ossie, he said, developers can define a metric once and treat it as a versioned, reviewable code artifact [14].
I think the analysts' hedge is correct. They said the backing makes interoperable analytics platforms a little more likely and is no guarantee that vendor lock-in will go away [2]. The converter savings follow from the design [18]. Whether lock-in eases depends on the vendor-specific calculations. Those move only as far as the format and the destination platform allow [8]. Michael Leone, principal analyst at Moor Strategy and Insights, said the bigger advantage of the backing is that making semantic models more portable gives enterprises more ownership of them [17].
What to watch
- Whether the Ossie specification adds DAX as a recognized query language, and whether non-Microsoft platforms can interpret DAX-defined metrics accurately.
- What Google says it will contribute once it finishes joining the project.
- How much of a Power BI model survives a round trip through Microsoft's two-way converter once it ships.
Clarity's read
What the record supports and how the coverage leans. The claims behind it follow.
Reality
- Evidence52
- Adoption18
- Hype gap+15
- Incentives60
- Confidence58
Perspective Coverage
4 publishers- Builder
- Builder 45%
- Operator
- Operator 34%
- Investor
- Investor 21%
Claim ledger
Ranked by verification strength, evidence, and original report placement.
- [1]
Microsoft and Google are joining a project to create an open specification for exchanging semantic models across data, analytics and AI platforms; the project already has the backing of over 60 companies including Databricks, Informatica, Mistral AI, Nvidia, Oracle, Salesforce and Snowflake.
- [2]
Analysts said Microsoft and Google's support makes it a little more likely that future analytics platforms will be interoperable, but is no guarantee that vendor lock-in will go away.
- [3]
Microsoft is pushing for the Ossie specification to include more support for its ontologies and for Ossie's recognized query languages to include DAX, the expression language Power BI uses for defining calculations and business metrics.
- [4]
Microsoft wrote that enterprises could carry the calculation logic that gives their semantic models business meaning alongside the underlying model when moving between platforms that support Ossie.
- [5]
Google is in the process of joining Apache Ossie, a company representative said via email; the company has not yet provided details on what it plans to contribute or has already contributed.
- [6]
The Ossie specification lists BigQuery/GoogleSQL as a supported dialect, a result of "early community contributions that recognize BigQuery's footprint across enterprise data stacks," the Google representative said.
- [7]
The project began as Open Semantic Interchange (OSI) and became Apache Ossie when it was accepted into the Apache Incubator in June.
- [8]
Walter said portability does not necessarily mean complete interoperability; how far enterprises can move semantic models depends on how much vendor-specific logic and functionality Ossie can represent and how accurately the destination platform can interpret it.
- [9]
Ossie uses JSON and YAML to represent semantic models, including datasets, fields, relationships, metrics and AI context.
- [10]
Ossie is meant to make semantic models interoperable across platforms such as Snowflake, Databricks, Tableau, ThoughtSpot and Sigma.
- [11]
Ossie uses a hub-and-spoke model: it is the common semantic format, and converters translate between it and individual vendors' semantic implementations, so an enterprise could move a model between compatible platforms without a separate point-to-point converter for every pair of vendors.
- [12]
Microsoft is developing a two-way converter between Power BI semantic models and Ossie, so semantic context defined in Power BI can be represented in the common format and Ossie models converted back into Power BI.
- [13]
Aditya Ranjan, senior data engineer at H-E-B, said support from the two companies could reduce the burden of repeated semantic engineering for enterprise teams moving analytics workloads between platforms.
- [14]
Ashish Chaturvedi, executive research leader at HFS Research, said recreating and maintaining the same business definitions across platforms often results in metric drift, and that with Ossie developers can define a metric once and treat it as a versioned, reviewable code artifact.
- [15]
Stephanie Walter of HyperFrame Research said maintaining one definition of a metric across platforms could reduce the risk of different AI agents interpreting the same metric differently, which could give CIOs more confidence to scale agentic deployments.
- [16]
Walter said portability gives buyers more leverage, since changing a BI or data platform would no longer require rebuilding the semantic layer from scratch.
- [17]
Michael Leone, principal analyst at Moor Strategy and Insights, said the bigger advantage of Microsoft and Google supporting Ossie is that it gives enterprises more ownership of their semantic models by making them more portable.
- [18]
For the five named platforms, point-to-point linking needs 10 two-way converters, while the hub design needs five.
- [19]
Adding Power BI to the five named platforms raises the point-to-point count to 15 two-way converters against six for the hub.
- [20]
Under the hub design, a semantic model moving between two vendor platforms passes through two conversions: from the source format into Ossie, then from Ossie into the destination format.
Sources
3 independent publishers whose own reporting we read for this story.
- benzinga.comGoogle Joining Industry Group Working to Help AI Better Understand Data - Benzinga
2 articles · September 29, 2026
- cio.comMicrosoft, Google back Apache Ossie to make enterprise data and AI platforms more interoperable | CIO
1 article · October 1, 2026
- dev.toMicrosoft and Google join Apache Ossie project
1 article · October 1, 2026
- infoworld.comMicrosoft, Google back Apache Ossie to make enterprise data and AI platforms more interoperable | InfoWorld
1 article · October 1, 2026
Topics and entities
Topics
- Proprietary Tooling and Vendor Lock-In
- Data interoperability standards
Entities
- Microsoft
- Snowflake
- Stephanie Walter
- HyperFRAME Research
- Ashish Chaturvedi
- Databricks
- Apache Software Foundation
- BigQuery
- Moor Strategy and Insights