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Mule is the runtime engine for Anypoint Platform™ and the industry's only runtime that can be used for a broad range of use cases from legacy, SaaS, and B2B integrations all the way to API implementation and management.

Single runtime

Handle any integration pattern  with one runtime for all your APIs and integrations.

Flexible deployment

Deploy on-premises, in the cloud, or take a hybrid approach.

Adaptable architecture

Implement event-driven, service-oriented, or microservice architectures.

What you can do with Mule runtime engine

Mule runtime engine screencap connect to any system

Connect to any system

Address any connectivity use case with a runtime that intelligently manages message routing, data mapping, orchestration, reliability, and security between systems and applications. Connect to common systems and databases with Anypoint Connectors, or use the Mule SDK to create customizable modules for integrating homegrown systems.

Ensure flexibility and high availability

Deploy on a runtime built with resiliency in mind to ensure uptime across any deployment, cloud, or on-premises. Upgrade without downtime by taking advantage of Mule’s classloader isolation, which separates runtime and app dependencies. Save valuable time when optimizing for performance with Mule’s dynamic self-tuning mechanism. 

Scale your architecture

Move millions of records between applications or data sources using Mule’s built-in batch integration capabilities, non-blocking I/O, or both. Every Mule runtime component has a clear role and is decoupled from any other component, allowing users to easily compose flows and account for future upgrades.
 

Mule ensure flexibility people illustration with cloud
Mule screencap map any data

Map and transform any data and format

Support a variety of transformations from and to any data type with DataWeave — from simple one-to-one mappings to elaborate transformations such as normalization, grouping, joins, partitioning, pivoting, and filtering.

Stream and handle data automatically

Get automatic streaming to handle content caching, larger than memory payloads, and closing of user streams. Stream and access data concurrently in order to process and transform information at scale.

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