Supports pipelines defined in a drag-and-drop manner on a clear GUI, template import and export, and multiple data sources and data processing activities.
Delivers diverse scheduling modes, such as periodic, event-driven, and manual and supports multiple execution policies, including precondition, timeout, and retry.
Supports dynamic creation and release of compute and storage resources, minimizing the DPS expenses.
Provides a unified console for obtaining pipeline status in real time and supports automatic retry and recovery of pipeline operations.
Pipelines that have complex service logics can be constructed. A pipeline consists of data sources and activities.
Supports a variety of data sources, such as OBS, MRS (HDFS and HBase), and RDS, and data processing activities, such as Spark, Hive, and SparkSQL.
Orchestrates pipelines through GUI-based drag-and-drop.
A pipeline can be scheduled on an hourly, daily, or weekly basis.
Periodic, event-driven, and manual scheduling modes help meet scheduling requirements for multiple applications.
Up to 20,000 IOPS and 350 MB/s throughput per disk.
Precondition, timeout, and retry execution policies facilitate execution of complex logics.
Provides visualized orchestration and supports multiple data sources and processing activities.
Provides diverse scheduling modes and execution policies.
Supports dynamic resource management to increase resource utilization while reducing usage costs.
Supports full-time hosting and monitors pipeline status in real time to ensure high reliability.