
The Big Data Platform supports manufacturing data and business teams in building and operating data-processing workflows. A decentralized architecture with high-availability support allows cluster expansion, while integration with Spark, Flink, Kettle, and DataX connects established big-data components.
Users can assemble workflows through visual drag-and-drop operation and run task types including SQL, Python, and Shell. The platform provides a shared environment for coordinating data tasks and scaling processing capacity as workload grows.




Adopting a decentralized design with high availability (HA) support to effectively prevent single points of failure, supporting non-stop expansion to guarantee business continuity.

Utilizing mainstream technical architectures with processing capacity scaling linearly with cluster size, seamlessly interfacing with mainstream big data components like Spark, Flink, Kettle, and DataX.

Offering visual operation that allows users to build complex workflows by dragging and dropping tasks, supporting SQL, Python, Shell, and other task types so business personnel can get started quickly.