Apache Doris
Apache Doris is a high-performance, real-time analytical database based on MPP (Massively Parallel Processing) architecture, governed by the Apache Software Foundation. It provides MySQL-protocol-compatible SQL queries, sub-second query latency on large-scale data, columnar storage with vectorized execution, real-time upsert via Stream Load and Routine Load APIs, and federated querying over data lakes (Hive, Iceberg, Hudi). It supports both shared-nothing and storage/compute-separated deployment modes.
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 Doris the way a machine reads it — 36 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 Doris scores 45.7/100 (developing), with a separate agent-readiness read of 7/100 (human only). 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 Doris
Each block below is one kind of artifact we hold for Apache Doris. 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 Doris
Apache Doris provides a MySQL-compatible protocol for SQL queries, a REST API for cluster management and monitoring, Stream Load HTTP API for real-time bulk data ingestion, Rout...
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 Doris 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 Doris Finops
FINOPSFeatures 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.
MPP Columnar Analytics
Massively parallel processing with columnar storage and vectorized execution engine for high-concurrency sub-second analytical queries.
Stream Load API
HTTP-based bulk data ingestion API that loads CSV, JSON, and Parquet data in real time with transactional guarantees.
MySQL Protocol Compatibility
Fully MySQL-wire-protocol compatible, enabling use of standard MySQL clients, drivers, and BI tools without modification.
Federated Data Lakehouse Queries
Query external data in Hive, Iceberg, Hudi, and Delta Lake tables without data movement using Multi-Catalog.
Real-Time Upsert (Unique Key Model)
Primary key based upsert model supports real-time CDC data ingestion with micro-second latency row-level updates.
Routine Load from Kafka
Continuous data ingestion from Apache Kafka topics with automatic offset management and exactly-once semantics.
Tiered Storage
Hot/warm/cold data tiering with object storage (S3, HDFS) for cost-optimized storage at scale.
MCP Server
Model Context Protocol (MCP) server enabling AI agents to query Doris databases through natural language.
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 Doris Context
JSON-LDSpectral 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 Doris API Rules
SPECTRALJSON Schema 3
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.
JSON Structure 3
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 Doris Routine Load Job Structure
JSON STRUCTUREApache Doris Stream Load Response Structure
JSON STRUCTUREApache Doris Table Schema Structure
JSON STRUCTUREExamples 3
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.
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 Dashboards and Reporting
Power business intelligence dashboards with sub-second query latency on live data updated continuously.
Log and Event Analytics
Ingest and analyze high-volume log, metric, and event data in real time using inverted indexes and full-text search.
Customer Data Platform
Consolidate customer behavioral and transactional data from multiple sources for real-time segmentation and analytics.
Data Lakehouse Analytics
Federate queries across data lake (Hive, Iceberg) and operational databases without ETL movement.
Ad-Hoc Analytics
Enable data analysts to run complex exploratory SQL queries on petabyte-scale datasets with fast response times.
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 Flink
Official Flink Connector for reading from and writing to Doris in real-time Flink streaming pipelines.
Apache Spark
Official Spark Connector for batch ETL and analytics workflows using Apache Spark.
Apache Kafka
Kafka Connector and Routine Load for continuous real-time data ingestion from Kafka topics.
Apache Iceberg / Hudi / Hive
Multi-Catalog feature enables federated queries over Iceberg, Hudi, and Hive Metastore data lakes.
Kubernetes
Official Kubernetes Operator for automated Doris cluster lifecycle management.
OpenTelemetry
OpenTelemetry demo integration for observability and tracing in Doris deployments.
Resources
Every other property we hold for Apache Doris — 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
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