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.
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
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.
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 COLLECTIONPricing 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
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.
Amazon Redshift Finops
FINOPSFeatures 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
JSON-LDAmazon Redshift Data 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.
Amazon Redshift API Rules
SPECTRALAmazon Redshift API Rules
SPECTRALJSON 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
JSON SCHEMAActiveStatementsExceededException
JSON SCHEMABatchExecuteStatementRequest
JSON SCHEMABatchExecuteStatementResponse
JSON SCHEMACancelStatementRequest
JSON SCHEMACancelStatementResponse
JSON SCHEMAColumnMetadata
JSON SCHEMADescribeStatementRequest
JSON SCHEMADescribeStatementResponse
JSON SCHEMADescribeTableRequest
JSON SCHEMADescribeTableResponse
JSON SCHEMAExecuteStatementRequest
JSON SCHEMAExecuteStatementResponse
JSON SCHEMAField
JSON SCHEMAGetStatementResultRequest
JSON SCHEMAGetStatementResultResponse
JSON SCHEMAInternalServerException
JSON SCHEMAListDatabasesRequest
JSON SCHEMAListDatabasesResponse
JSON SCHEMAListSchemasRequest
JSON SCHEMAListSchemasResponse
JSON SCHEMAListStatementsRequest
JSON SCHEMAListStatementsResponse
JSON SCHEMAListTablesRequest
JSON SCHEMAListTablesResponse
JSON SCHEMAResourceNotFoundException
JSON SCHEMASqlParameter
JSON SCHEMAStatementData
JSON SCHEMASubStatementData
JSON SCHEMATableMember
JSON SCHEMAValidationException
JSON SCHEMAScroll 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 Cancel Statement Request Structure
JSON STRUCTUREAmazon Redshift Data Cancel Statement Response Structure
JSON STRUCTUREAmazon Redshift Data Column Metadata Structure
JSON STRUCTUREAmazon Redshift Data Describe Table Request Structure
JSON STRUCTUREAmazon Redshift Data Describe Table Response Structure
JSON STRUCTUREAmazon Redshift Data Execute Statement Request Structure
JSON STRUCTUREAmazon Redshift Data Field Structure
JSON STRUCTUREAmazon Redshift Data Internal Server Exception Structure
JSON STRUCTUREAmazon Redshift Data List Databases Request Structure
JSON STRUCTUREAmazon Redshift Data List Databases Response Structure
JSON STRUCTUREAmazon Redshift Data List Schemas Request Structure
JSON STRUCTUREAmazon Redshift Data List Schemas Response Structure
JSON STRUCTUREAmazon Redshift Data List Statements Request Structure
JSON STRUCTUREAmazon Redshift Data List Statements Response Structure
JSON STRUCTUREAmazon Redshift Data List Tables Request Structure
JSON STRUCTUREAmazon Redshift Data List Tables Response Structure
JSON STRUCTUREAmazon Redshift Data Sql Parameter Structure
JSON STRUCTUREAmazon Redshift Data Statement Data Structure
JSON STRUCTUREAmazon Redshift Data Sub Statement Data Structure
JSON STRUCTUREAmazon Redshift Data Table Member Structure
JSON STRUCTUREAmazon Redshift Data Validation Exception Structure
JSON STRUCTUREScroll 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.
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 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
Access & Security 4
Authentication, authorization, and security posture
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