Goldman Sachs developed Legend internally, announced plans to contribute it to FINOS in November 2019, and open-sourced the platform in October 2020. Legend is a suite for data modeling, data access, and governance—not a finished hosted commercial service. The contribution made its software available for organizations and developers to explore, adapt, and contribute to through FINOS.
What Goldman Sachs contributed—and when
The announcement unfolded in two stages. At FINOS’s Open Source Strategy Forum on November 20, 2019, Goldman Sachs said it intended to contribute its internally developed platform. FINOS announced the open-source release in October 2020, making the distinction between an announced intention and software that had actually been released.
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The 2020 release covered five components: Legend Studio, Legend Engine, Legend SDLC, Legend Shared, and the Legend-PURE modeling language. FINOS describes Legend as available for anyone to use and contribute to; its project repository is licensed under Apache License 2.0. That describes the software’s open-source availability, not a guarantee that every deployment, dataset, or model is public. FINOS’s release announcement and the Legend project repository provide the project details.
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Legend is designed to help organizations describe data consistently, connect models to data sources, and manage access and governance. Rather than treating each dataset as an isolated technical resource, teams can define shared business concepts and use those models to support queries, APIs, and other data services.
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The main components
- Legend-PURE: the language for expressing data models and related logic.
- Legend Studio: the visual environment for creating and working with models.
- Legend Engine: the engine that executes model-based queries and services.
- Legend SDLC: tools for managing model development and its lifecycle.
- Legend Shared: a component included in the 2020 open-source release.
FINOS describes platform capabilities that include common vocabularies, access that respects entitlements in underlying sources, and formal constructs for ownership, validation, and provenance. Models can also be translated into formats including JSON Schema, Protobuf, and Avro. Those are stated capabilities and aims; they should not be mistaken for quantified evidence of efficiency gains or uniform results in every organization. See FINOS’s Legend overview for its description of the platform.
Why open-source a financial data modeling platform?
Financial institutions often need to represent overlapping concepts—such as trades, products, and business events—across teams and systems. A shared modeling approach can give those teams a common vocabulary and a way to collaborate on how concepts are represented. It can also help connect business definitions with the technical systems that store and serve data.
Goldman Sachs framed Legend as a way to connect business and engineering teams while supporting accurate, timely, and safe access to data. That is the company’s description of the platform’s purpose, not an independent measurement of outcomes. In the 2019 announcement, Goldman Sachs Chief Data Officer Neema Raphael said, “Open source technology is setting us on a path to greater collaboration and building mutual understanding.” FINOS’s 2019 contribution announcement records the statement.
Open source makes the software available for inspection, use, and contribution under its license. It does not remove the practical work of integrating systems, agreeing on definitions, setting governance policies, or deciding which models an organization can share.
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What the FINOS pilot showed
FINOS’s Legend Studio pilot gave participating financial institutions access to a shared Legend instance hosted on FINOS infrastructure. FINOS names Deutsche Bank, Morgan Stanley, and RBC Capital Markets among participants working on extensions to the ISDA Common Domain Model (CDM).
The CDM provides a common representation of financial products and events. In the pilot, Legend offered a shared environment for developing extensions to that model, illustrating how organizations could collaborate on financial concepts rather than each working entirely in isolation. The case study describes pilot participation; it does not establish that every participant adopted Legend in production or that the pilot produced measured business gains. FINOS’s Legend Studio Pilot case study gives the pilot details.
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Can anyone use Legend?
The software is open source, and FINOS presents it as available for anyone to use and contribute to. There are several ways to explore it, but they suit different purposes:
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| Route | What it offers | Important consideration |
|---|---|---|
| FINOS hosted Studio instance | A shared environment for collaborative modeling. | FINOS says it is free and intended for shared modeling work. Projects map to public GitLab projects, so it is not suitable for proprietary models. |
| Legend Omnibus | A local environment for trying Legend. | The getting-started guide says Omnibus requires Docker. |
| Development installation | An environment for development and configuration. | Setup and component requirements can change; use the current FINOS documentation. |
For hosted access, local setup, or development, start with FINOS’s getting-started guide. Check the current documentation for sign-up steps, commands, and component availability rather than relying on old setup instructions.
How Legend relates to the ISDA Common Domain Model
Legend is a platform for modeling and working with data; the ISDA CDM is a financial industry model that represents financial products and events. The pilot used Legend to develop extensions to the CDM. In practical terms, the CDM supplies shared domain definitions, while Legend supplies tools and an environment for expressing, managing, and using models.
That relationship does not mean Legend and the CDM are interchangeable, or that using Legend automatically makes an organization’s data interoperable. Teams still need to map their systems and data to the concepts they choose to model and establish suitable governance.
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