Apache Oozie
Apache Oozie is a workflow scheduler system for managing Apache Hadoop jobs. It enables users to define workflows as directed acyclic graphs (DAGs) of actions including MapReduce, Pig, Hive, Sqoop, and custom Java/shell steps. Coordinator jobs trigger workflows based on time schedules or data availability, while bundle jobs group multiple coordinators. Oozie provides a REST API for job submission, lifecycle management, monitoring, and system administration. Governed by the Apache Software Foundation under the Apache License 2.0, written in Java.
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 Oozie the way a machine reads it — 59 machine-readable artifacts across 4 APIs, 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 Oozie scores 58.3/100 (developing), with a separate agent-readiness read of 39/100 (agent aware). 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 Oozie
Each block below is one kind of artifact we hold for Apache Oozie. 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 4
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 Oozie Admin API
System administration, configuration, and monitoring
Apache Oozie Job API
Single job lifecycle management and information retrieval
Apache Oozie Jobs API
Job submission and bulk management
Apache Oozie Versions API
Supported protocol version discovery
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 Oozie 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.
Apache Oozie Finops
FINOPSFeatures 10
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.
Directed Acyclic Graph Workflows
Define complex data processing pipelines as DAGs of actions executed on Apache Hadoop.
Coordinator Jobs
Schedule recurring workflows triggered by time intervals or data availability conditions in HDFS.
Bundle Jobs
Group multiple coordinator jobs into a single bundle for coordinated lifecycle management.
REST API Management
Full REST API for job submission, lifecycle control, monitoring, and system administration.
Native Hadoop Action Types
Built-in support for MapReduce, Pig, Hive, Sqoop, Distcp, and custom Java/shell actions.
SLA Management
Define and monitor service level agreements on workflow and coordinator actions with alert capabilities.
DAG Visualization
Generate PNG, SVG, or DOT graph visualizations of workflow DAGs for debugging and documentation.
Log Retrieval
Retrieve execution logs, error logs, and audit trails for jobs via REST API with filtering support.
High Availability
Built-in HA support with multiple Oozie server instances and distributed state management.
Shared Library Support
Manage shared Hadoop libraries across workflows for consistent classpath management.
Scroll within the panel for all 10 ·
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.
Apache Oozie Context
JSON-LDSpectral Rules 2
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 Oozie API Rules
SPECTRALApache Oozie API Rules
SPECTRALJSON Schema 8
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.
BuildVersion
JSON SCHEMAJobAction
JSON SCHEMAJobId
JSON SCHEMAJobInfo
JSON SCHEMAJobList
JSON SCHEMASystemMetrics
JSON SCHEMASystemStatus
JSON SCHEMAValidationResult
JSON SCHEMAScroll within the panel for all 8 ·
JSON Structure 8
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 Oozie Build Version Structure
JSON STRUCTUREApache Oozie Job Action Structure
JSON STRUCTUREApache Oozie Job Id Structure
JSON STRUCTUREApache Oozie Job Info Structure
JSON STRUCTUREApache Oozie Job List Structure
JSON STRUCTUREApache Oozie System Metrics Structure
JSON STRUCTUREApache Oozie System Status Structure
JSON STRUCTUREApache Oozie Validation Result Structure
JSON STRUCTUREScroll within the panel for all 8 ·
Examples 8
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.
Apache Oozie Job Id Example
EXAMPLEScroll within the panel for all 8 ·
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.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 6
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.
ETL Pipeline Orchestration
Orchestrate multi-step ETL pipelines combining Hive queries, MapReduce jobs, and data transfers on Hadoop.
Scheduled Data Processing
Run recurring Hadoop batch jobs on time-based schedules using coordinator jobs.
Data-Triggered Workflows
Trigger workflows automatically when new data arrives in HDFS using coordinator data-in conditions.
Machine Learning Pipeline Automation
Automate ML model training and evaluation pipelines on Hadoop with dependency chaining.
Data Migration and Archival
Orchestrate large-scale data migration, compaction, and archival workflows across Hadoop clusters.
Multi-Cluster Coordination
Coordinate workflows that span multiple Hadoop clusters using Distcp and remote actions.
Integrations 6
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 Hadoop
Core integration with HDFS for data storage and YARN for resource management.
Apache Hive
Native Hive action type for executing HiveQL queries as workflow steps.
Apache Pig
Native Pig action type for data transformation scripts in workflow pipelines.
Apache Sqoop
Native Sqoop action type for importing and exporting data between Hadoop and RDBMS.
Apache Spark
Spark action type for running Spark jobs within Oozie workflows.
Apache MapReduce
Native MapReduce action type as the foundational Hadoop computation framework.
Resources
Every other property we hold for Apache Oozie — 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 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 3
Pagination, idempotency, versioning, errors, and events
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 3
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
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