WhaleScheduler: Enterprise Big Data Workflow Scheduling Platform(BYOL)

Overview

WhaleScheduler is a commercial version of high-performance distributed, easy-to-use, low-code data scheduling product created by the core team of Apache DolphinScheduler. It provides a more powerful scheduling engine, dozens of scheduling job types, simple IDE editing interface, rich scheduling and running functions, scheduling lineage analysis, operation and maintenance monitoring and enterprise-level permission control. It has been widely used in actual business in many industries, can meet complex scheduling scenarios such as finance, telecommunications, retail, and the Internet, and supports multiple fields such as databases, cloud, big data, AI, MLOps, etc., helping enterprises to quickly improve data development efficiency.

Highlights

• Visual, Drag& Drop Design: A drag and drop interface that enables both engineers and data analysts to build complex ETL pipelines or Task Orchestration.

• Rich Task Ecosystem and Connectors: Supports 30 plus task types(SQL, Shell, Python, java, etc.) and 290 plus data sources (databases, SaaS, data lakes, etc.) out of the box, allowing fast orchestration & integration.

• Deep Observability and Runtime Control: Enhanced monitoring, alerting, and manual intervention capabilities make it easy to ensure pipeline reliability and reduce operational risk.

Supported Cloud Infrastructure

• Amazon Web Services (AWS): Full support via AWS Marketplace, including AMIs (Amazon Machine Images) and CloudFormation templates for automated deployment.

• Google Cloud Platform (GCP): Support for GCE (Google Compute Engine) and GKE (Google Kubernetes Engine) deployments.

• Alibaba Cloud: High-performance integration for regional data centers, including support for MaxCompute and OSS.

• Huawei Cloud: Optimized for enterprise Big Data environments and cloud-native application stacks.

• Tencent Cloud: Support for hybrid cloud orchestration and large-scale data synchronization.