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Amazon Redshift website screenshot

Amazon Redshift

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools.

agent ready

Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.

Kin Score

API Evangelist profiles Amazon Redshift the way a machine reads it — 120 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 — Amazon Redshift scores 65.3/100 (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 Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 65.3/100 · strong
Contract Quality 17.0 / 25
Developer Ergonomics 8.7 / 20
Commercial Clarity 15.8 / 20
Operational Transparency 6.2 / 13
Governance 8.8 / 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 Amazon Redshift

Each block below is one kind of artifact we hold for Amazon Redshift. 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.

Amazon Redshift Serverless API

The Amazon Redshift Serverless API for managing serverless data warehouse workgroups, namespaces, and capacity without provisioning clusters.

Amazon Redshift Metadata API

List databases, schemas, and tables in a Redshift data warehouse

Amazon Redshift Result Retrieval API

Retrieve results from completed SQL statement executions

Amazon Redshift Statement Execution API

Execute SQL statements against Amazon Redshift clusters or serverless workgroups

Amazon Redshift Statement Management API

Describe, list, and cancel SQL statement executions

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).

Amazon Redshift Data 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.

Amazon Redshift 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 6

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.

Massively Parallel Processing

Distributed query execution across multiple nodes for petabyte-scale analytics with sub-second response times.

Serverless Data Warehouse

Auto-scaling compute capacity without cluster provisioning, paying only for compute used during queries.

Data API

Run SQL statements without managing database connections using IAM-based authentication and asynchronous execution.

Federated Query

Query data across Amazon RDS, Aurora, and S3 data lakes without moving data using federated query capabilities.

Machine Learning Integration

Build, train, and deploy ML models directly in Redshift using SQL with Amazon SageMaker integration.

Concurrency Scaling

Automatically add transient capacity to handle bursts of concurrent queries without performance degradation.

Semantic Vocabularies 2

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.

Amazon Redshift Context

0 classes · 6 properties

JSON-LD

Amazon Redshift Data Context

0 classes · 0 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.

Amazon Redshift API Rules

6 rules · 4 warnings

SPECTRAL

Amazon Redshift API Rules

15 rules · 8 errors · 6 warnings

SPECTRAL

JSON Schema 31

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.

Amazon Redshift Cluster

32 properties

JSON SCHEMA

ActiveStatementsExceededException

1 properties

JSON SCHEMA

BatchExecuteStatementRequest

9 properties

JSON SCHEMA

BatchExecuteStatementResponse

7 properties

JSON SCHEMA

CancelStatementRequest

1 properties

JSON SCHEMA

CancelStatementResponse

1 properties

JSON SCHEMA

ColumnMetadata

13 properties

JSON SCHEMA

DescribeStatementRequest

1 properties

JSON SCHEMA

DescribeStatementResponse

19 properties

JSON SCHEMA

DescribeTableRequest

9 properties

JSON SCHEMA

DescribeTableResponse

3 properties

JSON SCHEMA

ExecuteStatementRequest

10 properties

JSON SCHEMA

ExecuteStatementResponse

7 properties

JSON SCHEMA

Field

6 properties

JSON SCHEMA

GetStatementResultRequest

2 properties

JSON SCHEMA

GetStatementResultResponse

4 properties

JSON SCHEMA

InternalServerException

1 properties

JSON SCHEMA

ListDatabasesRequest

7 properties

JSON SCHEMA

ListDatabasesResponse

2 properties

JSON SCHEMA

ListSchemasRequest

8 properties

JSON SCHEMA

ListSchemasResponse

2 properties

JSON SCHEMA

ListStatementsRequest

5 properties

JSON SCHEMA

ListStatementsResponse

2 properties

JSON SCHEMA

ListTablesRequest

9 properties

JSON SCHEMA

ListTablesResponse

2 properties

JSON SCHEMA

ResourceNotFoundException

2 properties

JSON SCHEMA

SqlParameter

2 properties

JSON SCHEMA

StatementData

12 properties

JSON SCHEMA

SubStatementData

11 properties

JSON SCHEMA

TableMember

3 properties

JSON SCHEMA

ValidationException

1 properties

JSON SCHEMA

Scroll within the panel for all 31 ·

JSON Structure 30

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.

Amazon Redshift Data Field Structure

6 properties

JSON STRUCTURE

Scroll within the panel for all 30 ·

Examples 30

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 30 ·

Security Posture 4

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.

Amazon Redshift Authentication

apiKey · 1 scheme

SECURITY

Amazon Redshift Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Amazon Redshift Vulnerability Disclosure

security.txt · contact published

SECURITY

Amazon Redshift Trust Center

PCI DSS, HIPAA, FedRAMP, GDPR, FIPS 140

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.

Amazon Redshift Agentic Access

10 operations · 10 acting

10 operations · 10 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.

Business Intelligence Analytics

Run complex analytical queries across petabytes of structured data for BI dashboards and reporting.

Data Lake Analytics

Query data directly in Amazon S3 using Redshift Spectrum without loading it into the warehouse.

Real-Time Analytics

Ingest streaming data and run near-real-time analytics on operational data for instant insights.

ETL Pipeline Processing

Transform and load large datasets using SQL-based ETL operations within the data warehouse.

Serverless Ad-Hoc Queries

Run on-demand analytical queries without provisioning clusters using Redshift Serverless and Data API.

Resources

Every other property we hold for Amazon Redshift — 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

Operate 3

Status, limits, changes, and where to get help

Commercial 3

Pricing, plans, and the legal terms of use

Company 1

The organization behind the API

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