Legend
Legend is an open-source data management and modeling platform (data modeling and governance) hosted by FINOS and used to define, govern, and consume complex data across financial and enterprise environments.
- Open-source platform for collaborative data modeling and governance (data modeling)
- Centralized definition of data types, models, and semantics for shared understanding (data governance)
- Tools for authoring, versioning, and publishing data models and logic (model lifecycle management)
- Execution of queries and transformations based on defined models and mappings (data integration and query execution)
- Support for multi-stakeholder collaboration across business, technology, and operations teams (collaboration tooling)
More About Legend
Legend is an open-source data management and modeling platform (data modeling and governance) under the Fintech Open Source Foundation (FINOS), created to support collaborative definition, governance, and usage of complex data across financial services and other data-intensive enterprises.
The platform focuses on establishing a shared data language by allowing users to define domain models, data types, and business concepts in a structured way (data modeling). These models can be governed centrally and reused across systems and teams, which supports alignment between business stakeholders and technical implementations (data governance). Legend provides authoring tools that run in a browser, enabling users to create and maintain models, mappings, and data transformations in a controlled environment, with support for versioning and lifecycle management (model lifecycle management).
Legend includes capabilities to connect logical models to physical data sources through mappings (data integration). Users can define how conceptual data elements Marketing Automation Platform (MAP) onto concrete schemas and storage structures, and then execute queries and transformations based on those mappings (query and transformation execution). The platform supports execution engines that interpret the models and mappings to generate queries against underlying data sources, enabling model-driven retrieval and processing rather than hard-coded data access (model-driven integration).
In enterprise environments, Legend is positioned for use in complex regulatory, risk, and analytics contexts where consistent data definitions and traceability are required (regulatory data management). It supports collaboration among business analysts, data modelers, quants, developers, and operations teams by providing shared workspaces, permission controls, and governance workflows (collaboration and access control). Because it is hosted within FINOS, Legend is designed for deployment within financial institutions and integration with existing tooling and infrastructure (enterprise integration).
Architecturally, Legend is described as a modular platform with components for model authoring, model storage, execution, and integration with external systems (platform architecture). It uses a modeling language and metamodel to describe data structures, relationships, and functions in a technology-agnostic way (domain-specific modeling language). Interoperability is enabled through APIs and integration points that allow other systems to consume models, execute queries, or embed Legend capabilities within broader data platforms (API-based integration).
Within an enterprise taxonomy, Legend fits into categories such as data modeling, metadata management, and data governance, with additional relevance for regulatory reporting, analytics, and model-driven application development. Its role is to provide a shared, version-controlled, and executable representation of data and logic that can be used consistently across applications, teams, and business processes.