Apache Kylin
Apache Kylin is an open-source distributed analytics engine designed to provide a SQL interface and multi-dimensional analysis (OLAP) on large-scale datasets. It provides sub-second query latency on trillion-record datasets via pre-computed cubes and works on top of Hadoop, Spark, and cloud storage.
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 Kylin the way a machine reads it — 59 machine-readable artifacts across 7 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 Kylin scores 58.8/100 (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
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Apache Kylin
Each block below is one kind of artifact we hold for Apache Kylin. 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 7
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 Kylin JDBC Driver
The Kylin JDBC driver provides SQL-over-Kylin access for BI tools and SQL clients, enabling standard JDBC connectivity to Kylin OLAP cubes.
Apache Kylin Authentication API
User authentication
Apache Kylin Jobs API
Build job management
Apache Kylin Models API
Data model management
Apache Kylin Projects API
Project management
Apache Kylin Query API
SQL query execution
Apache Kylin Tables API
Table and datasource management
Scroll within the panel for all 7 ·
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 Kylin 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 Kylin Finops
FINOPSFeatures 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.
Sub-Second OLAP Queries
Pre-computed cubes enable sub-second query response on trillion-record datasets.
SQL Interface
ANSI SQL interface for business analysts using existing SQL skills.
Cube Pre-computation
Build cubes with aggregates pre-calculated for instant query response.
Hadoop and Cloud Integration
Works on top of Hadoop, Spark, and cloud object storage.
JDBC/ODBC Drivers
Standard JDBC and ODBC drivers for BI tool integration.
Segment Management
Incremental cube building with date-range segment management.
Multi-Tenancy
Project-based multi-tenancy for isolating datasets and access.
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.
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 Kylin API Rules
SPECTRALApache Kylin 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.
AuthResponse
JSON SCHEMAJob
JSON SCHEMAModel
JSON SCHEMAProjectRequest
JSON SCHEMAProject
JSON SCHEMAQueryRequest
JSON SCHEMAQueryResponse
JSON SCHEMATable
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.
Rest Api Auth Response Structure
JSON STRUCTURERest Api Job Structure
JSON STRUCTURERest Api Model Structure
JSON STRUCTURERest Api Project Request Structure
JSON STRUCTURERest Api Project Structure
JSON STRUCTURERest Api Query Request Structure
JSON STRUCTURERest Api Query Response Structure
JSON STRUCTURERest Api Table 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.
Rest Api Job Example
EXAMPLERest Api Model Example
EXAMPLERest Api Project Example
EXAMPLERest Api Table Example
EXAMPLEScroll within the panel for all 8 ·
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 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 Warehouse Query Acceleration
Accelerate slow Hive or Spark queries with Kylin cube pre-computation.
BI Tool Integration
Connect Tableau, PowerBI, and Superset to Kylin via JDBC for analytics.
Real-Time OLAP
Stream data into Kylin incrementally for near-real-time OLAP analytics.
Large-Scale Reporting
Generate business reports over trillion-record datasets in seconds.
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 Hadoop
Reads from HDFS and executes MapReduce cube builds on Hadoop.
Apache Spark
Spark-based cube building for faster and more efficient data processing.
Apache Hive
Hive metastore integration for table schema and metadata.
Apache HBase
HBase storage for pre-computed cube data.
Tableau
Native Tableau connector via Kylin JDBC driver.
Apache Superset
Apache Superset integration via JDBC for self-service analytics.
Scroll within the panel for all 7 ·
Resources
Every other property we hold for Apache Kylin — 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 3
Authentication, authorization, and security posture
Commercial 1
Pricing, plans, and the legal terms of use
← All providers · Data indexed from github.com/api-evangelist/apache-kylin · machine-readable index on apis.io