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Apache Druid

Apache Druid is a high-performance, real-time analytics database governed by the Apache Software Foundation, designed for fast slice-and-dice OLAP queries on event-time data. It features a distributed, column-oriented storage engine with automatic rollup, supports both streaming (Kafka, Kinesis) and batch (S3, HDFS, local) data ingestion, and provides a SQL query interface plus a native JSON query API via REST. Druid is optimized for sub-second queries at petabyte scale with high concurrency.

agent aware

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 Druid the way a machine reads it — 42 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 Druid scores 50.7/100 (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.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 50.7/100 · developing
Contract Quality 13.5 / 25
Developer Ergonomics 6.1 / 20
Commercial Clarity 7.9 / 20
Operational Transparency 4.8 / 13
Governance 10.4 / 12
Discoverability 8.0 / 10
Agent readiness — 39/100 · agent aware
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 15
MCP Server 0 / 12
Machine-Readable Auth 0 / 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 Druid

Each block below is one kind of artifact we hold for Apache Druid. 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 Druid Druid API

The Druid API from Apache Druid — 10 operation(s) for druid.

Open Collections 1

Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

Apache Druid REST API

OPEN COLLECTION

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 Druid 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 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.

Sub-Second OLAP Queries

Columnar storage with bitmap indexes, dictionary encoding, and pre-aggregation (rollup) enables sub-second queries on billions of events.

Druid SQL API

REST endpoint for submitting standard SQL queries with ANSI SQL support, time-based filtering, and streaming response options.

Native JSON Query API

Druid-native query format (Timeseries, TopN, GroupBy, Scan, Search) for maximum control and performance.

Streaming Ingestion

Real-time data ingestion from Apache Kafka and Amazon Kinesis with supervisor-managed offset tracking and exactly-once semantics.

Batch Ingestion

Parallel batch indexing tasks from local files, S3, GCS, HDFS, and other external storage systems.

Automatic Rollup

Pre-aggregates metrics at ingestion time to reduce storage and query time, configurable per datasource.

Time-Based Partitioning

All data is partitioned by time interval (segments), enabling efficient time-range query pruning.

Multi-Tenancy

Query isolation and resource management via query lanes, scheduler priorities, and row-level access control.

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.

Apache Druid Context

5 classes · 32 properties

JSON-LD

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 Druid API Rules

5 rules · 3 warnings

SPECTRAL

JSON 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.

IngestionTask

9 properties

JSON SCHEMA

SqlQueryRequest

7 properties

JSON SCHEMA

SqlQueryResponse

5 properties

JSON SCHEMA

Supervisor

8 properties

JSON SCHEMA

JSON 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 Druid Ingestion Task Structure

9 properties

JSON STRUCTURE

Apache Druid Sql Query Request Structure

7 properties

JSON STRUCTURE

Apache Druid Sql Query Response Structure

5 properties

JSON STRUCTURE

Apache Druid Supervisor Structure

8 properties

JSON STRUCTURE

Examples 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.

Apache Druid Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Apache Druid 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 Druid Agentic Access

13 operations · 11 acting

13 operations · 11 acting

AGENTIC

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.

Real-Time Event Analytics

Analyze click streams, IoT events, application logs, and user behavior data with sub-second query latency.

Business Intelligence Dashboards

Power interactive BI dashboards with high-concurrency low-latency queries backed by Druid's columnar engine.

Network and Security Monitoring

Ingest and analyze network flow data and security events in real time for threat detection and capacity planning.

Ad Tech Analytics

Process advertising impression, click, and conversion events at high volume with real-time aggregation.

Operational Analytics

Monitor application performance metrics and operational data with drilldown and filtering capabilities.

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 Kafka

KafkaSupervisor for real-time continuous ingestion from Kafka topics into Druid datasources.

Amazon Kinesis

KinesisSupervisor for real-time data ingestion from AWS Kinesis data streams.

Apache Hadoop / HDFS

Native Hadoop batch indexing task for bulk loading data from HDFS or MapReduce job outputs.

Amazon S3 / GCS

Batch and streaming ingestion from object storage (S3, GCS, Azure Blob) using index tasks.

Apache Hive

Druid-Hive integration for querying Druid datasources from HiveQL and performing joins.

Kubernetes

Official Kubernetes operator for deploying and managing Druid clusters on Kubernetes.

Imply (Commercial)

Imply provides a commercial managed Druid service with additional features and enterprise support.

Scroll within the panel for all 7 ·

Resources

Every other property we hold for Apache Druid — 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

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 1

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

Operate 1

Status, limits, changes, and where to get help

Company 1

The organization behind the API

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