spark
Apache DolphinScheduler is an open-source distributed workflow orchestration platform with visual DAG interfaces for managing complex data tasks.
Score
60
User Rating
3.0
Free/Trial Support
Supported
Starting Price
--
Last Updated
Aug 04, 2026
Overview
What is spark?
Apache DolphinScheduler is a distributed and extensible open-source workflow orchestration platform that provides powerful DAG visual interfaces to manage and schedule tasks like Spark, Flink, and Hive jobs. It supports low-code drag-and-drop workflows and high-performance execution with features like cross-project dependencies, task isolation, and version control.
What is spark used for?
Top Features
- Visual DAG workflow design
- Support for 30+ job types (e.g., Spark, Flink, Hive)
- Decentralized multi-master/worker architecture
- Task isolation with tenant and worker groups
- Workflow version control and data backfill
- Drag-and-drop and code-based workflow creation
How to use spark?
Users can create workflows by dragging and dropping tasks in a visual interface or coding with Python, YAML, or Open API. It supports decentralized multi-master/worker design for high concurrency, allows task management (kill, pause, resume), and includes data backfill and workflow version control for batch processing.
Alternative Tools
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Pros & Cons
Pros
- Open-source and free to use
- High scalability and reliability
- User-friendly visual interface
- Supports complex task dependencies and isolation
- Active community and extensive documentation
Cons
- Requires technical expertise for deployment and setup
- May have a learning curve for advanced features
Use Cases
- Orchestrating big data pipelines (e.g., ETL processes)
- Managing distributed computing tasks in data science
- Automating IT operations and workflow scheduling
- Handling high-concurrency data processing in enterprises
spark Pricing
Free Plan
No detailed pricing information available
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