Introduction
Data Virtualization enables real-time access to your FME workflows — no duplication, no delay, just live data on demand.
It lays the groundwork for OpenAPI REST APIs that turn those workflows into shareable data services for web apps, enterprise systems, and AI tools.
By exposing FME workflows as secure, reusable API endpoints, teams can automate data sharing, integrate systems in real time, and deliver consistent information without manual exports or custom scripts.
With built-in support for OpenAPI, caching, and asynchronous processing, FME Flow makes it easy to build fast, reliable, enterprise-grade APIs.
If you are unfamiliar with the basics of REST APIs or how HTTP requests work, review those concepts before working with Data Virtualization. Understanding fundamentals like endpoints, request methods (such as GET and POST), and response formats (like JSON) will make the material easier to follow. There are many excellent resources available online from providers such as Mozilla, Postman, and Amazon Web Services.
Why Use Data Virtualization?
FME’s Data Virtualization provides a flexible, no-code platform for connecting all your data, applications, and AI systems through APIs.
It brings the benefits of integration, automation, and governance together — helping teams make faster, more informed decisions.
Key Benefits
- Faster Decision-Making: Give teams instant, secure access to live data without duplication or ETL delays.
- Lower Operational Costs: Stream data directly from the source, reducing infrastructure and development effort.
- Better Governance and Security: Use authenticated access to protect sensitive data while ensuring compliance and interoperability with modern and legacy systems.
- Higher Productivity: Enable both technical and non-technical users to build and deploy APIs in a no-code environment.
- All-Data, Any-AI: Connect every system, application, and AI model to the data it needs — securely, efficiently, and in real time.
When to Use Data Virtualization
Use Data Virtualization when you need to connect systems, automate workflows, or provide consistent, real-time access to information.
It’s ideal for organizations looking to modernize data sharing without replacing existing systems or building custom middleware.
Common Scenarios
- Delivering live data to internal applications, dashboards, or web services.
- Sharing standardized information across departments, partners, or public portals.
- Powering AI and analytics workflows that rely on structured, always-current data.
- Providing secure, role-based access to operational or environmental datasets.
Data Virtualization is used across industries — from government and utilities to finance and healthcare — to make critical information accessible while maintaining control and compliance.
How Data Virtualization Works
Data Virtualization acts as a bridge between your data and the systems that need it.
Each API you build in FME Flow connects directly to one or more FME Workspaces, which handle data access, transformation, and delivery.
When someone makes a request to the API, FME Flow runs the connected workspace in real time, processes the data, and returns the results in the requested format.
This means your APIs always serve up-to-date information — without exporting, syncing, or maintaining separate copies of data.
FME Flow automatically documents every API using OpenAPI standards and provides an integrated Swagger interface for testing, sharing, and exploration.
Technical Capabilities
FME Flow’s Data Virtualization feature provides a complete framework for building, managing, and scaling REST APIs.
It supports the full range of standards and controls needed for secure, high-performance, and enterprise-grade integrations.
API Design and Structure
- Supports standard HTTP methods (GET, POST, PUT, PATCH, DELETE)
- Customize path, query, and header parameters
- Defines structured request and response schemas for validation
- Configures custom headers, content types, and response formats
- Supports structured file handling for uploads and downloads
Security and Governance
- Integrates with FME Flow roles, users, and API tokens.
- Supports CORS configuration, versioning, and namespace management
- Provides custom status codes and error responses for consistent feedback
Performance and Reliability
- Enables caching to speed up responses and reduce load
- Runs asynchronous requests for long or complex jobs
- Delivers OpenAPI-compliant documentation automatically
- Connects directly to FME Workspaces for real-time data access and transformation
Integration and Compatibility
- Works with JSON, GeoJSON, XML, CSV, and files
- Fully OpenAPI (OAS) compatible for external integration
- Designed to complement Webhook URLs and the FME Flow REST API for complete system interoperability
Articles
Core Data Virtualization Tutorial Series
A guided, step-by-step learning path for building APIs in FME Flow.
Beginner
1. Create a Data Virtualization API
Learn how to define a new API in FME Flow.
2. Create a Manual Endpoint in Data Virtualization
Create a static response endpoint directly in the FME Flow interface, suitable for metadata or simple status checks.
3. Secure Data Virtualization Endpoints with Authentication
Configure endpoint-level access using roles and API tokens. Understand how authentication works in Data Virtualization.
4. Creating a Workspace Response for a Data Virtualization GET Endpoint
Using the entire FME Platform, create and author a workspace response for a GET endpoint.
Intermediate
5. Enhancing Data Virtualization Endpoints with Parameters
Design endpoints with request parameters to give users more control over the data they access and how it's returned.
6. Create a POST Endpoint in a Data Virtualization API
Create a POST endpoint that accepts structured data, validates the input using a defined schema, and stores it in a database using a workspace in FME Flow.
Data Virtualization Use Cases and Advanced Topics
Explore how Data Virtualization connects to real-world applications, AI, and system automation.
7. Working with Files in Data Virtualization APIs
Create a POST endpoint that accepts and returns a file.
8. Working with OpenAPI Specification Files in Data Virtualization
Import or export OpenAPI Specification files to define Data Virtualization APIs and enable integration with tools like the OpenAPICaller.
9. Webhook Verification Using Data Virtualization
See how to verify and manage webhook calls through FME Flow’s Data Virtualization for secure, event-driven integrations.
10. Using Data Virtualization With Generative AI
Explore how Data Virtualization connects FME workflows with AI models to deliver live, structured data for intelligent automation.
Additional Resources
Blog Post: How to build scalable APIs and apps using Data Virtualization in FME
Blog post on creating fast, secure, and scalable APIs from FME Workspaces using caching, asynchronous processing, and Data Virtualization.
Webinar: Data Virtualization in Action: Scaling APIs and Apps with FME
See how organizations use FME Flow’s Data Virtualization to build scalable APIs and applications that deliver real-time, trusted data anywhere it’s needed.
Webinar: Data Virtualization: Bringing the Power of FME to Any Application
Discover how Data Virtualization extends FME’s integration power across systems, enabling live data access for web, mobile, and enterprise applications.