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spark

spark

Apache DolphinScheduler is an open-source distributed workflow orchestration platform with visual DAG interfaces for managing complex data tasks.

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Score
60
User Rating
3.0
Free/Trial Support
Supported
Starting Price
--
Last Updated
Aug 04, 2026
OverviewTop featuresHow to usePros & consWho usesUse casesPricingAlternative toolsUser reviews0

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?

Data Integration

Tags

Workflow Orchestrationdag-visualizationLow CodeOpen Sourcedistributed-schedulingData PipelineBig Data
spark cover

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

No alternative tools found

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

User Reviews

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