Amazon DocumentDB
Amazon DocumentDB is a fully managed, MongoDB-compatible document database service that makes it easy to set up, operate, and scale MongoDB-compatible databases in the cloud. DocumentDB is designed from the ground up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale.
Reference-quality API operations across every facet — a rich contract, published governance, transparent operations, and machine-readable commercial terms.
API Evangelist profiles Amazon DocumentDB the way a machine reads it — 48 machine-readable artifacts across 4 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 DocumentDB scores 73.3/100 (exemplar), 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 Amazon DocumentDB
Each block below is one kind of artifact we hold for Amazon DocumentDB. 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 4
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 DocumentDB Amazon DocumentDB API API
The Amazon DocumentDB API API from Amazon DocumentDB — 1 operation(s) for amazon documentdb api.
Amazon DocumentDB #CreateDBInstance API
The #CreateDBInstance API from Amazon DocumentDB — 1 operation(s) for #createdbinstance.
Amazon DocumentDB #DeleteDBCluster API
The #DeleteDBCluster API from Amazon DocumentDB — 1 operation(s) for #deletedbcluster.
Amazon DocumentDB #DescribeDBInstances API
The #DescribeDBInstances API from Amazon DocumentDB — 1 operation(s) for #describedbinstances.
Postman Collections 1
A runnable collection turns the contract into something a developer can execute in seconds. We profile them because the fastest way to trust an API is to make a real call against it.
Ready-to-run Postman collections for exercising this provider's APIs.
Amazon DocumentDB API
POSTMANOpen 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 DocumentDB API
OPEN COLLECTIONArazzo Workflows 6
Real integrations are rarely a single call. Arazzo describes the multi-step sequences — auth, then create, then confirm — so both a human and an agent can follow the choreography, not just the endpoints.
Multi-step API workflows described with the Arazzo specification.
Amazon DocumentDB Add Instance and Await Available
Add an instance to an existing cluster and poll until the instance is available.
ARAZZOAmazon DocumentDB Bootstrap Cluster with Primary Instance
Create a cluster, wait until available, then add and await a primary instance.
ARAZZOAmazon DocumentDB Decommission Cluster with Final Snapshot
Verify a cluster exists, delete it with a final snapshot, then poll until it is gone.
ARAZZOAmazon DocumentDB Inventory Cluster and Instances
Describe a cluster, then describe a member instance and the wider instance fleet.
ARAZZOAmazon DocumentDB Provision Cluster and Await Available
Create a DocumentDB cluster and poll until it reports the available status.
ARAZZOAmazon DocumentDB Scale Out Read Replica
Add a replica instance to a cluster, wait for it, then confirm cluster membership.
ARAZZOPricing 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 Documentdb 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 Documentdb 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.
Serverless Architecture
Automatically scales capacity up or down in fine-grained increments based on application demand, with up to 90% cost savings versus peak provisioning.
MongoDB Compatibility
Migrate applications typically without code changes or downtime using existing MongoDB drivers and tools.
Global Clusters
Automatically replicates data across up to 10 AWS Regions for low-latency reads and disaster recovery.
Fully Managed
Eliminates database patching, backups, and monitoring overhead so you can focus on application development.
I/O-Optimized Storage
Provides up to 40% cost savings for I/O-intensive workloads with predictable pricing.
Memory-Optimized Instances
Offers memory-optimized instance types with up to 43% cost savings for large workloads.
Automated Backups
Continuous backups to Amazon S3 and point-in-time recovery within the backup retention window.
Encryption at Rest and in Transit
Data is encrypted using AES-256, with support for AWS KMS customer-managed keys.
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.
Amazon Documentdb 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 DocumentDB API Rules
SPECTRALAmazon DocumentDB API Rules
SPECTRALJSON 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.
Amazon DocumentDB DBCluster
JSON SCHEMACreateDBClusterResult
JSON SCHEMADBCluster
JSON SCHEMADescribeDBClustersResult
JSON SCHEMAJSON 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.
Amazon Documentdb Dbcluster Structure
JSON STRUCTUREDocumentdb Openapi Create Db Cluster Result Structure
JSON STRUCTUREDocumentdb Openapi Db Cluster Structure
JSON STRUCTUREDocumentdb Openapi Describe Db Clusters Result Structure
JSON STRUCTUREExamples 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 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.
Content Management Systems
Store and retrieve flexible JSON-structured content with rich query capabilities for CMS platforms.
E-Commerce Platforms
Manage product catalogs, user profiles, and order data with scalable document storage.
Mobile and Web Applications
Power real-time application backends with low-latency, scalable document storage.
Generative AI Applications
Store and retrieve context, embeddings, and conversational history for AI-powered agentic applications.
Gaming Applications
Handle player profiles, leaderboards, and game state with flexible schema and high throughput.
Resources
Every other property we hold for Amazon DocumentDB — 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 5
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 8
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 8 ·
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 6
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 4
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/amazon-documentdb · machine-readable index on apis.io