Coordinate multiple instances and form a cluster in a simple and transparent way, without affecting your current developments.
Cluster-wide concurrency control. Control concurrent processes in a simple way when scaling the system, both horizontally and vertically: lock, semaphore and CountDownLatch.
Distributed data structures. Share data between applications and scale processes transparently using distributed and concurrency-ready high-level data structures.
Distributed data sources. Distribute data through the whole cluster and balance the workload.
Distributed scopes. Optimize and enrich your processes with advanced operations like transaction and cache scopes.
Harnesses the capabilities of the distributed persistence of data.
Distributes queues and optimizes load balance.
Safely runs scheduled jobs, cluster-wide.
Design batch processes whose performance will scale horizontally as the workload is distributed to the chosen cluster nodes.
Communication between different Mule versions. A great help when migrating from Mule's version 3 to version 4.
Communication between applications implemented in different languages. Python, Node, PHP, .Net, Java...
Design your own data ingestion processes following a simple interface, and seamlessly integrate them into your system to achieve real-time data processing.
Use well-known languages - standard SQL and Lucene text query - to access data within your cluster.
Complete distributed file system API.
Integrate your Mule applications with Open Data services (OData).
Integrate your Mule applications with TransferWise services.
Integrate your Mule applications with SAP ERP Central Component (ECC).