Apache DolphinScheduler

Apache DolphinScheduler is a modern distributed and extensible data orchestration platform governed by the Apache Software Foundation. It provides a DAG-based visual workflow designer, multi-master/multi-worker architecture for horizontal scaling, and a comprehensive REST API for programmatic control. It supports dozens of task types (Shell, Spark, Flink, SQL, Python, HTTP, etc.), multi-cloud deployments, multi-tenancy, backfill, and a Python SDK (PyDolphinScheduler).

Apache DolphinScheduler is listed with 1 API on the APIs.io network. Tagged areas include Apache, DAG, Data Pipeline, Open Source, and Orchestration.

The Apache DolphinScheduler catalog on APIs.io includes 1 JSON-LD context and 1 Spectral governance ruleset.

Apache DolphinScheduler’s developer surface includes developer portal, documentation, getting-started guide, and 17 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

32.6/100 thin ▬ flat Agent 2/100 human only self hosted · Apache-2.0 Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessFreemium

1 API 8 Features 5 Use Cases

Apache DAG Data Pipeline Open Source Orchestration Python Scheduling Workflows

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 32.6/100 · thin

Contract Quality 6.2 / 19

Developer Ergonomics 2.5 / 15

Access Clarity 1.2 / 15

Operational Transparency 3.6 / 10

Contract Governance 0.9 / 9

Discoverability 4.3 / 8

Regulatory Posture 2.5 / 15

Open Source Surface 10.0 / 10

Agent readiness — 2/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 7 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Open Source Surface applies to this provider. This product is open source and we read its repository directly, so Open Source Surface carries 10 points of the composite. It is scored from what the repository actually publishes — a security policy, a contribution guide, a release history, a code of conduct — read live from the provider rather than inferred from our own catalog pointers. This facet adds; nothing was taken away to make room for it. An open-source project is not excused from the commercial facets, because exemption would strip it of the points it does earn. If we have the wrong repository, or this product is not open source, say so on your provider repo and we will drop the facet rather than have you publish against it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 75 points between them, because both conditional facets apply and carry 25 points together. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes

11 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Access Clarity scores 7.9 — up to +18.4 composite points
Developer Ergonomics scores 16.7 — up to +16.7 composite points
Contract Quality scores 33.2 — up to +16.7 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/apache-dolphinscheduler/apis.yml: open an issue on github.com/api-evangelist/apache-dolphinscheduler to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

Apache DolphinScheduler REST API

The DolphinScheduler REST API enables programmatic management of projects, workflow definitions (DAGs), workflow instances, task types, schedules, resources, data sources, alert...

Apache DolphinScheduler API pricing

Not yet checked against Apache DolphinScheduler's own pricing page. Compiled by API Evangelist on 2026-05-04; confirm before you rely on a figure. A free plan or tier is listed.

Plan	Price
Free freemium	Free
Professional paid	Free
Enterprise enterprise	—

Plan details, limits and sources →

Rate limits

Free Tier Default: 10 requests per minute
Free Tier Monthly Quota: 1000 requests per month
Professional Tier Default: 100 requests per minute

Compiled by API Evangelist, not yet checked against Apache DolphinScheduler's documentation. All 5 limits →

Pricing Plans 1

Published pricing tiers and plan structures.

Apache Dolphinscheduler Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Apache Dolphinscheduler Rate Limits

5 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Apache Dolphinscheduler Finops

FINOPS

Features 8

Notable capabilities this provider offers.

DAG Visual Workflow Designer

Web-based drag-and-drop interface for building directed acyclic graph (DAG) workflows with real-time execution visualization.

REST Open API

Comprehensive REST API for all platform operations including workflow management, scheduling, resource management, and administration.

Multi-Master/Worker Architecture

Decentralized architecture with horizontal scaling support, capable of processing tens of millions of tasks per day.

Rich Task Types

Built-in task types including Shell, Spark, Flink, SQL, Python, HTTP, DataX, Seatunnel, Jupyter, and custom task plugins.

Multi-Tenancy

Supports multiple tenants with isolated resource quotas, permissions, and workflow namespaces.

Workflow Versioning

Version control for workflow definitions and instances, enabling rollback and auditing of workflow changes.

Data Source Management

Unified data source management supporting MySQL, PostgreSQL, Hive, Trino, Spark, ClickHouse, and many other databases.

Python SDK

PyDolphinScheduler allows defining and managing workflows programmatically in Python with code-first workflow authoring.

Scroll for all 8

Semantic Vocabularies 1

JSON-LD contexts and semantic vocabularies used across these APIs.

Apache Dolphinscheduler Context

6 classes · 29 properties

JSON-LD

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

Apache DolphinScheduler — jsonschema rules

5 rules · 3 warnings 2 info

SPECTRAL

JSON Schema 4

Standalone JSON Schema definitions for this provider's data models.

Schedule

9 properties

JSON SCHEMA

TaskDefinition

12 properties

JSON SCHEMA

WorkflowDefinition

12 properties

JSON SCHEMA

WorkflowInstance

10 properties

JSON SCHEMA

JSON Structure 4

JSON Structure definitions describing this provider's data shapes.

Apache Dolphinscheduler Schedule Structure

9 properties

JSON STRUCTURE

Apache Dolphinscheduler Task Definition Structure

12 properties

JSON STRUCTURE

Apache Dolphinscheduler Workflow Definition Structure

12 properties

JSON STRUCTURE

Apache Dolphinscheduler Workflow Instance Structure

10 properties

JSON STRUCTURE

Examples 4

Example request and response payloads for these APIs.

Apache Dolphinscheduler Schedule Example

9 fields

EXAMPLE

Apache Dolphinscheduler Task Definition Example

12 fields

EXAMPLE

Apache Dolphinscheduler Workflow Definition Example

12 fields

EXAMPLE

Apache Dolphinscheduler Workflow Instance Example

10 fields

EXAMPLE

Security Posture 2

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Apache Dolphinscheduler Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Apache Dolphinscheduler Vulnerability Disclosure

security.txt · contact published

SECURITY

Use Cases 5

What developers build with this provider.

Data Pipeline Orchestration

Orchestrate complex ETL/ELT data pipelines with dependencies, retries, and monitoring across distributed systems.

Machine Learning Workflows

Schedule and manage ML model training, evaluation, and deployment pipelines with task dependencies.

Multi-Cloud Data Workflows

Orchestrate workflows spanning multiple cloud providers and data centers with unified scheduling.

SQL and Analytics Scheduling

Schedule recurring SQL queries, reports, and analytics jobs against multiple data sources.

DevOps and CI/CD Pipelines

Automate deployment workflows, data quality checks, and operational tasks with DolphinScheduler DAGs.

Integrations 7

Pre-built integrations with other platforms and tools.

Apache Spark

Native Spark task type for submitting Spark batch and streaming jobs from DolphinScheduler workflows.

Apache Flink

Native Flink task type for submitting Flink stream processing jobs.

Apache Hive

Hive data source and task type for SQL-on-Hadoop workloads.

Kubernetes

Kubernetes deployment mode and K8s task type for container-native workflow execution.

Docker

Official Docker images and Docker Compose configuration for rapid deployment.

DataX / SeaTunnel

Native task types for DataX and SeaTunnel data integration frameworks.

Apache Airflow

An Airflow provider package allows triggering DolphinScheduler workflows from Airflow DAGs.

Scroll for all 7

Resources

Get Started 2

Portal, sign-up, and the first successful call

Portal

Portal

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

ContributionGuide

ContributionGuide

Documentation

Documentation

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Vocabulary

Vocabulary

Build 4

SDKs, sample code, and the tooling you integrate with

CodeOfConduct

CodeOfConduct

GitHubOrganization

GitHubOrganization

GitHubRepository

GitHubRepository

PyDolphinScheduler Python SDK

SDKs

Access & Security 3

Authentication, authorization, and security posture

SecurityPolicy

SecurityPolicy

VulnerabilityDisclosure

VulnerabilityDisclosure

DomainSecurity

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

RateLimits

RateLimits

IssueTracker

IssueTracker

Releases

Releases

Commercial 3

Pricing, plans, and the legal terms of use

Plans

Plans

FinOps

FinOps

License

License

Company 2

The organization behind the API

Website

Website

LinkedIn

Source (apis.yml)

aid: apache-dolphinscheduler
name: Apache DolphinScheduler
description: Apache DolphinScheduler is a modern distributed and extensible data orchestration platform governed by the Apache
  Software Foundation. It provides a DAG-based visual workflow designer, multi-master/multi-worker architecture for horizontal
  scaling, and a comprehensive REST API for programmatic control. It supports dozens of task types (Shell, Spark, Flink, SQL,
  Python, HTTP, etc.), multi-cloud deployments, multi-tenancy, backfill, and a Python SDK (PyDolphinScheduler).
type: Index
deliveryModel:
  model: self-hosted
  license: Apache-2.0
  open_source: true
  commercial: false
  callable_host: false
  label: Self-hosted open source · you run it yourself
  confidence: high
  source:
  - license
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: low
  source:
  - plans
  - security
  generated: '2026-11-06'
  method: derived
position: Consuming
access: 3rd-Party
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/apache-dolphinscheduler.png
tags:
- Apache
- DAG
- Data Pipeline
- Open Source
- Orchestration
- Python
- Scheduling
- Workflows
tags_raw:
- Apache
- DAG
- Data Pipeline
- Open Source
- Orchestration
- Python
- Scheduling
- Workflow
- Open-Source
created: '2026-03-16'
modified: '2026-04-19'
url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/apis.yml
specificationVersion: '0.23'
apis:
- aid: apache-dolphinscheduler:apache-dolphinscheduler-rest-api
  name: Apache DolphinScheduler REST API
  description: The DolphinScheduler REST API enables programmatic management of projects, workflow definitions (DAGs), workflow
    instances, task types, schedules, resources, data sources, alerts, tenants, and users. Authentication is via API token.
    A Swagger UI is available at /dolphinscheduler/swagger-ui/index.html.
  humanURL: https://dolphinscheduler.apache.org/en-us/docs/latest/user_doc/guide/open-api.html
  tags:
  - Alerts
  - DAG
  - Data Sources
  - Project
  - REST
  - Resources
  - Scheduling
  - Task
  - Tenants
  - Workflows
  tags_raw:
  - Alerts
  - DAG
  - Data Sources
  - Projects
  - REST
  - Resources
  - Scheduling
  - Tasks
  - Tenants
  - Workflow
  properties:
  - type: Documentation
    url: https://dolphinscheduler.apache.org/en-us/docs/latest/user_doc/guide/open-api.html
  - type: GettingStarted
    url: https://dolphinscheduler.apache.org/en-us/docs/latest/user_doc/start/quick-start.html
  - type: GitHubRepository
    url: https://github.com/apache/dolphinscheduler
  - type: SDKs
    url: https://pypi.org/project/apache-airflow-providers-apache-dolphinscheduler/
    title: Python SDK (PyDolphinScheduler)
  - type: Tools
    url: https://hub.docker.com/r/apache/dolphinscheduler-standalone-server
    title: Docker Image
  - type: Tools
    url: https://github.com/apache/dolphinscheduler-operator
    title: Kubernetes Operator
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-schema/apache-dolphinscheduler-schedule-schema.json
    title: Schedule
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-schema/apache-dolphinscheduler-task-definition-schema.json
    title: Task Definition
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-schema/apache-dolphinscheduler-workflow-definition-schema.json
    title: Workflow Definition
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-schema/apache-dolphinscheduler-workflow-instance-schema.json
    title: Workflow Instance
  - type: JSONStructure
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-structure/apache-dolphinscheduler-schedule-structure.json
  - type: JSONStructure
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-structure/apache-dolphinscheduler-task-definition-structure.json
  - type: JSONStructure
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-structure/apache-dolphinscheduler-workflow-definition-structure.json
  - type: JSONStructure
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-structure/apache-dolphinscheduler-workflow-instance-structure.json
  - type: JSONLD
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/json-ld/apache-dolphinscheduler-context.jsonld
  - type: Examples
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/examples/apache-dolphinscheduler-schedule-example.json
  - type: Examples
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/examples/apache-dolphinscheduler-task-definition-example.json
  - type: Examples
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/examples/apache-dolphinscheduler-workflow-definition-example.json
  - type: Examples
    url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/examples/apache-dolphinscheduler-workflow-instance-example.json
maintainers:
- FN: Kin Lane
  email: info@apievangelist.com
common:
- type: Plans
  url: plans/apache-dolphinscheduler-plans-pricing.yml
- type: RateLimits
  url: rate-limits/apache-dolphinscheduler-rate-limits.yml
- type: FinOps
  url: finops/apache-dolphinscheduler-finops.yml
- type: Website
  url: https://www.apache.org/
- type: IssueTracker
  url: https://github.com/apache/dolphinscheduler/issues
- type: Releases
  url: https://github.com/apache/dolphinscheduler/releases
- type: SecurityPolicy
  url: https://github.com/apache/dolphinscheduler/blob/dev/SECURITY.md
- type: CodeOfConduct
  url: https://github.com/apache/.github/blob/main/.github/CODE_OF_CONDUCT.md
- type: ContributionGuide
  url: https://github.com/apache/dolphinscheduler/blob/dev/CONTRIBUTING.md
- type: License
  name: Apache-2.0
  url: https://github.com/apache/dolphinscheduler/blob/dev/LICENSE
- type: VulnerabilityDisclosure
  url: security/apache-dolphinscheduler-vulnerability-disclosure.yml
- type: DomainSecurity
  url: security/apache-dolphinscheduler-domain-security.yml
- type: LinkedIn
  url: https://www.linkedin.com/company/apache-dolphinscheduler
- type: Portal
  url: https://dolphinscheduler.apache.org/
- type: Documentation
  url: https://dolphinscheduler.apache.org/en-us/docs/latest/
- type: GettingStarted
  url: https://dolphinscheduler.apache.org/en-us/docs/latest/user_doc/start/quick-start.html
- type: GitHubOrganization
  url: https://github.com/apache
- type: GitHubRepository
  url: https://github.com/apache/dolphinscheduler
- type: SDKs
  url: https://github.com/apache/dolphinscheduler-sdk-python
  title: PyDolphinScheduler Python SDK
- type: Features
  data:
  - name: DAG Visual Workflow Designer
    description: Web-based drag-and-drop interface for building directed acyclic graph (DAG) workflows with real-time execution
      visualization.
  - name: REST Open API
    description: Comprehensive REST API for all platform operations including workflow management, scheduling, resource management,
      and administration.
  - name: Multi-Master/Worker Architecture
    description: Decentralized architecture with horizontal scaling support, capable of processing tens of millions of tasks
      per day.
  - name: Rich Task Types
    description: Built-in task types including Shell, Spark, Flink, SQL, Python, HTTP, DataX, Seatunnel, Jupyter, and custom
      task plugins.
  - name: Multi-Tenancy
    description: Supports multiple tenants with isolated resource quotas, permissions, and workflow namespaces.
  - name: Workflow Versioning
    description: Version control for workflow definitions and instances, enabling rollback and auditing of workflow changes.
  - name: Data Source Management
    description: Unified data source management supporting MySQL, PostgreSQL, Hive, Trino, Spark, ClickHouse, and many other
      databases.
  - name: Python SDK
    description: PyDolphinScheduler allows defining and managing workflows programmatically in Python with code-first workflow
      authoring.
- type: UseCases
  data:
  - name: Data Pipeline Orchestration
    description: Orchestrate complex ETL/ELT data pipelines with dependencies, retries, and monitoring across distributed
      systems.
  - name: Machine Learning Workflows
    description: Schedule and manage ML model training, evaluation, and deployment pipelines with task dependencies.
  - name: Multi-Cloud Data Workflows
    description: Orchestrate workflows spanning multiple cloud providers and data centers with unified scheduling.
  - name: SQL and Analytics Scheduling
    description: Schedule recurring SQL queries, reports, and analytics jobs against multiple data sources.
  - name: DevOps and CI/CD Pipelines
    description: Automate deployment workflows, data quality checks, and operational tasks with DolphinScheduler DAGs.
- type: Integrations
  data:
  - name: Apache Spark
    description: Native Spark task type for submitting Spark batch and streaming jobs from DolphinScheduler workflows.
  - name: Apache Flink
    description: Native Flink task type for submitting Flink stream processing jobs.
  - name: Apache Hive
    description: Hive data source and task type for SQL-on-Hadoop workloads.
  - name: Kubernetes
    description: Kubernetes deployment mode and K8s task type for container-native workflow execution.
  - name: Docker
    description: Official Docker images and Docker Compose configuration for rapid deployment.
  - name: DataX / SeaTunnel
    description: Native task types for DataX and SeaTunnel data integration frameworks.
  - name: Apache Airflow
    description: An Airflow provider package allows triggering DolphinScheduler workflows from Airflow DAGs.
- type: Vocabulary
  url: https://raw.githubusercontent.com/api-evangelist/apache-dolphinscheduler/refs/heads/main/vocabulary/apache-dolphinscheduler-vocabulary.yaml

Apache DolphinScheduler API — frequently asked questions

Does Apache DolphinScheduler have an API?

Yes. APIs.io lists 1 API from Apache DolphinScheduler, including Apache DolphinScheduler REST API.

How much does the Apache DolphinScheduler API cost?

APIs.io lists 3 pricing plans for Apache DolphinScheduler, with each plan's price, limits and inclusions under Pricing on this page.

Is the Apache DolphinScheduler API ready for AI agents?

Apache DolphinScheduler has a Kin Score of 32.6 out of 100 (thin) and an Agent Readiness score of 1.9 (human-only), scored by API Evangelist on 2026-11-06.

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