1
Harnesses the capabilities of the distributed persistence of data.
2
Safely runs scheduled jobs, cluster-wide.
3
Designs batch processes whose performance will scale horizontally as the workload is distributed to the chosen cluster nodes.
4
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...
5
Design your own data ingestion processes following a simple interface inside your Mule applications, and seamlessly integrate them into your system to achieve real-time data processing.
6
Use well-known languages - standard SQL and Lucene text query - to access data within your cluster.
7
Complete distributed file system API.
8
Integrate your Mule applications with Open Data services (OData).
9
Integrate your Mule applications with TransferWise services.
10
Integrate your Mule applications with SAP ERP Central Component (ECC).