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).
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles Apache DolphinScheduler the way a machine reads it — 40 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Apache DolphinScheduler scores 48.0/100 (developing), with a separate agent-readiness read of 7/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
How we profile Apache DolphinScheduler
Each block below is one kind of artifact we hold for Apache DolphinScheduler. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 1
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
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...
Pricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Apache Dolphinscheduler Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Features 8
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
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 within the panel for all 8 ·
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Spectral Rules 1
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
Apache DolphinScheduler API Rules
SPECTRALJSON Schema 4
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
Schedule
JSON SCHEMATaskDefinition
JSON SCHEMAWorkflowDefinition
JSON SCHEMAWorkflowInstance
JSON SCHEMAJSON Structure 4
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Apache Dolphinscheduler Schedule Structure
JSON STRUCTUREApache Dolphinscheduler Task Definition Structure
JSON STRUCTUREApache Dolphinscheduler Workflow Definition Structure
JSON STRUCTUREApache Dolphinscheduler Workflow Instance Structure
JSON STRUCTUREExamples 4
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Security Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Use Cases 5
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
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 tell you where this provider already fits in a stack.
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 within the panel for all 7 ·
Resources
Every other property we hold for Apache DolphinScheduler — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 2
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Design & Contract 1
Pagination, idempotency, versioning, errors, and events
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Company 1
The organization behind the API
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