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Apache Ranger website screenshot

Apache Ranger

Apache Ranger is a framework to enable, monitor, and manage comprehensive data security across the Hadoop platform. It provides centralized security administration for fine-grained authorization policies across Hadoop ecosystem components.

agent ready

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.

Kin Score

API Evangelist profiles Apache Ranger the way a machine reads it — 70 machine-readable artifacts across 5 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 Ranger scores 51.9/100 (developing), with a separate agent-readiness read of 48/100 (agent ready). 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.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 51.9/100 · developing
Contract Quality 16.2 / 25
Developer Ergonomics 3.9 / 20
Commercial Clarity 7.9 / 20
Operational Transparency 4.8 / 13
Governance 10.4 / 12
Discoverability 8.8 / 10
Agent readiness — 48/100 · agent ready
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 15
MCP Server 0 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 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

How we profile Apache Ranger

Each block below is one kind of artifact we hold for Apache Ranger. 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 5

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 Ranger Audit API

The Audit API from Apache Ranger — 1 operation(s) for audit.

Apache Ranger Groups API

The Groups API from Apache Ranger — 1 operation(s) for groups.

Apache Ranger Policies API

The Policies API from Apache Ranger — 2 operation(s) for policies.

Apache Ranger Services API

The Services API from Apache Ranger — 2 operation(s) for services.

Apache Ranger Users API

The Users API from Apache Ranger — 1 operation(s) for users.

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 Ranger Rate Limits

5 limits

RATE LIMITS

FinOps 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 7

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.

Centralized Policy Management

Manage security policies for all Hadoop services from a single interface

Fine-Grained Access Control

Column-level, row-level, and data masking policies for Hive and HBase

Attribute-Based Access Control

Context-aware policies based on user attributes and tag classifications

Audit Logging

Comprehensive audit trail of all resource access events

Multi-Service Support

Supports HDFS, Hive, HBase, Kafka, Storm, Solr, Kudu, and more

LDAP/AD Integration

Sync users and groups from Active Directory or LDAP

Security Zones

Delegate policy administration with security zones

Scroll within the panel for all 7 ·

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 Ranger Context

13 classes · 42 properties

JSON-LD

Spectral 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 Ranger API Rules

5 rules · 3 warnings

SPECTRAL

Apache Ranger API Rules

15 rules · 5 errors · 9 warnings

SPECTRAL

JSON Schema 13

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.

AccessType

2 properties

JSON SCHEMA

AuditEntry

12 properties

JSON SCHEMA

AuditList

2 properties

JSON SCHEMA

GroupList

2 properties

JSON SCHEMA

PolicyItem

4 properties

JSON SCHEMA

PolicyList

4 properties

JSON SCHEMA

PolicyResource

3 properties

JSON SCHEMA

Policy

9 properties

JSON SCHEMA

RangerGroup

4 properties

JSON SCHEMA

RangerService

6 properties

JSON SCHEMA

RangerUser

7 properties

JSON SCHEMA

ServiceList

2 properties

JSON SCHEMA

UserList

2 properties

JSON SCHEMA

Scroll within the panel for all 13 ·

JSON Structure 13

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 Ranger Access Type Structure

2 properties

JSON STRUCTURE

Apache Ranger Audit Entry Structure

12 properties

JSON STRUCTURE

Apache Ranger Audit List Structure

2 properties

JSON STRUCTURE

Apache Ranger Group List Structure

2 properties

JSON STRUCTURE

Apache Ranger Policy Item Structure

4 properties

JSON STRUCTURE

Apache Ranger Policy List Structure

4 properties

JSON STRUCTURE

Apache Ranger Policy Resource Structure

3 properties

JSON STRUCTURE

Apache Ranger Policy Structure

9 properties

JSON STRUCTURE

Apache Ranger Ranger Group Structure

4 properties

JSON STRUCTURE

Apache Ranger Ranger Service Structure

6 properties

JSON STRUCTURE

Apache Ranger Ranger User Structure

7 properties

JSON STRUCTURE

Apache Ranger Service List Structure

2 properties

JSON STRUCTURE

Apache Ranger User List Structure

2 properties

JSON STRUCTURE

Scroll within the panel for all 13 ·

Examples 13

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.

Scroll within the panel for all 13 ·

Security Posture 3

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.

Apache Ranger Authentication

http · 1 scheme

SECURITY

Apache Ranger Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Apache Ranger Vulnerability Disclosure

security.txt · contact published

SECURITY

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.

Apache Ranger Agentic Access

13 operations · 6 acting

13 operations · 6 acting

AGENTIC

Use Cases 4

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 Lake Security

Enforce column and row-level security on Hadoop data lake

Regulatory Compliance

Meet GDPR, HIPAA, and SOX requirements with audit logs and masking

Multi-Tenant Authorization

Isolate access between teams and business units

Kafka Topic Authorization

Control which applications can produce and consume Kafka topics

Integrations 5

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

Native HDFS and YARN authorization integration

Apache Hive

Column-level and row-level security for Hive queries

Apache HBase

Table and column family security for HBase

Apache Kafka

Topic-level authorization for Kafka producers and consumers

Apache Atlas

Tag-based policies using Atlas data classifications

Resources

Every other property we hold for Apache Ranger — 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.

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 1

SDKs, sample code, and the tooling you integrate with

← All providers · Data indexed from github.com/api-evangelist/apache-ranger · machine-readable index on apis.io