Apache Atlas
Apache Atlas is a scalable and extensible set of core foundational data governance services developed by the Apache Software Foundation. It enables enterprises to effectively meet their compliance requirements within Hadoop and allows integration with the whole enterprise data ecosystem. Atlas provides metadata management, data classification, lineage tracking, business glossary, and a REST API for programmatic governance operations. It supports discovery, auditing, and policy management for enterprise data assets.
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
API Evangelist profiles Apache Atlas the way a machine reads it — 72 machine-readable artifacts across 6 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 Atlas scores 60.2/100 (strong), 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
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Apache Atlas
Each block below is one kind of artifact we hold for Apache Atlas. 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 6
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 Atlas Discovery API
Search and discover metadata entities using various search strategies.
Apache Atlas Entities API
Manage metadata entities (CRUD operations on Atlas entities).
Apache Atlas Glossary API
Manage business glossary terms and categories.
Apache Atlas Lineage API
Track data lineage and provenance between entities.
Apache Atlas Relationships API
Manage relationships between entities.
Apache Atlas Types API
Manage type definitions including entity types, classifications, and relationships.
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 Atlas 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 Atlas 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.
Metadata Management
Centrally manage metadata for enterprise data assets including Hive tables, HDFS files, Kafka topics, HBase tables, and Spark jobs.
Data Classification
Apply classification tags to data assets for sensitivity classification (PII, PHI, confidential) and policy enforcement.
Data Lineage Tracking
Automatically capture and visualize data lineage across data pipeline stages for impact analysis and compliance.
Business Glossary
Manage a centralized business glossary of terms and categories to standardize data definitions across the organization.
REST API
Comprehensive REST API for programmatic metadata management, discovery, lineage retrieval, and type definition management.
Search and Discovery
Find data assets using basic, full-text, DSL, and attribute-based search across all registered metadata.
Policy-Based Data Access
Integrate with Apache Ranger for attribute-based access control policies driven by Atlas classification tags.
Auditing
Comprehensive audit trail of all metadata changes and entity operations for compliance and governance.
Hook-Based Metadata Collection
Hooks for Hive, HBase, Sqoop, Storm, and other Hadoop ecosystem tools for automatic metadata harvesting.
Type System
Extensible type system for defining custom entity types, classification types, and relationship types.
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 Atlas 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 Atlas API Rules
SPECTRALApache Atlas API Rules
SPECTRALJSON Schema 11
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.
AtlasEntitiesWithExtInfo
JSON SCHEMAAtlasEntity
JSON SCHEMAAtlasEntityWithExtInfo
JSON SCHEMAAtlasErrorResponse
JSON SCHEMAAtlasGlossary
JSON SCHEMAAtlasLineageInfo
JSON SCHEMAAtlasRelationship
JSON SCHEMAAtlasSearchResult
JSON SCHEMAAtlasTypesDef
JSON SCHEMAEntityMutationResponse
JSON SCHEMAEntityWithExtInfo
JSON SCHEMAScroll within the panel for all 11 ·
JSON Structure 11
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.
Atlas Atlas Entities With Ext Info Structure
JSON STRUCTUREAtlas Atlas Entity Structure
JSON STRUCTUREAtlas Atlas Entity With Ext Info Structure
JSON STRUCTUREAtlas Atlas Error Response Structure
JSON STRUCTUREAtlas Atlas Glossary Structure
JSON STRUCTUREAtlas Atlas Lineage Info Structure
JSON STRUCTUREAtlas Atlas Relationship Structure
JSON STRUCTUREAtlas Atlas Search Result Structure
JSON STRUCTUREAtlas Atlas Types Def Structure
JSON STRUCTUREAtlas Entity Mutation Response Structure
JSON STRUCTUREAtlas Entity With Ext Info Structure
JSON STRUCTUREScroll within the panel for all 11 ·
Examples 11
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.
Atlas Atlas Entity Example
EXAMPLEAtlas Atlas Glossary Example
EXAMPLEScroll within the panel for all 11 ·
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.
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.
Data Governance and Compliance
Track data assets, apply classifications, and enforce policies for GDPR, HIPAA, and CCPA compliance.
Data Lineage Analysis
Trace data from source to consumption to understand pipeline impact and debug data quality issues.
Metadata-Driven Data Discovery
Enable data consumers to find relevant datasets using classification-based and attribute-based search.
Data Catalog Integration
Serve as the metadata backbone for enterprise data catalogs and data mesh architectures.
Sensitive Data Identification
Classify PII and sensitive data assets and integrate with Ranger for attribute-based access control.
Business Glossary Management
Maintain standard business definitions and link them to technical metadata for consistent data interpretation.
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 Hive
Native Hive hook for automatic metadata harvesting of Hive databases, tables, and query lineage.
Apache Ranger
Integration with Ranger for policy-based data access control driven by Atlas classification tags.
Apache Kafka
Kafka hook for tracking Kafka topics and message schema metadata.
Apache HBase
HBase hook for capturing table and namespace metadata.
Apache Spark
Spark integration for capturing dataset and job-level lineage from Spark applications.
Apache Sqoop
Sqoop hook for importing relational database metadata and lineage into Atlas.
Cloudera Data Platform
Native integration with Cloudera Data Platform (CDP) as the metadata management backbone.
Scroll within the panel for all 7 ·
Resources
Every other property we hold for Apache Atlas — 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 2
Pagination, idempotency, versioning, errors, and events
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 3
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
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