Apache Spark vs Helidon comparison

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

Helidon is a lightweight framework that enables developers to build microservices in Java. It caters to various primary use cases, such as developing RESTful APIs, creating cloud-native applications, implementing microservices architectures, and building lightweight and reactive applications. 

Helidon's standout attributes include its seamless and effective development of lightweight, scalable applications, support for multiple programming languages, strong focus on performance, and comprehensive documentation with helpful community support. 

Users have found Helidon beneficial for their organizations, enhancing productivity, streamlining processes, improving collaboration, and facilitating better communication. It also increases efficiency, reduces errors, enhances decision-making, and promotes overall growth and success.