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APIs / Storage / Amazonaws / AWS RDS Data API
AWS RDS Data API logo

AWS RDS Data API

Browse all Amazonaws APIs
62
AI ReadinessAI-Aware (B-)62/100
See full scorecard
Agent-ready OpenAPI document · curated by JenticStorageDatabasehmac6 EndpointsREST

Know of an official OpenAPI document? Contribute it →

For Agents

Run SQL and parameterized batch statements against Aurora Serverless and Aurora DSQL clusters over HTTPS without managing connections.

Use for: I need to run a SELECT against an Aurora Serverless cluster, Insert a row into an Aurora table from a Lambda function, Execute a batch of INSERTs with parameter sets in one call, Begin a transaction on an Aurora cluster and run multiple statements

Not supported: Does not provision databases, manage schemas via DDL workflows, or run SQL on non-Aurora engines - use for HTTPS SQL execution on Aurora Serverless and Aurora DSQL clusters only.

Jentic publishes the only available OpenAPI specification for the AWS RDS Data API, keeping it validated and agent-ready. The RDS Data API runs SQL against Aurora Serverless and Aurora DSQL clusters over HTTPS without persistent database connections or VPC connectivity, using IAM and Secrets Manager for authentication. Six operations cover single-statement execution, batch parameterized execution, transaction begin and commit and rollback, and a legacy ExecuteSql endpoint. It is the right fit for serverless functions, mobile clients, and AI agents that need ad-hoc SQL access without managing a connection pool.

Jentic One on GithubView OpenAPI Document

Install Jentic One Beta

Connect the AWS RDS Data API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the AWS RDS Data API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

1

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Famazonaws.com%2Frds-data" | sh
2

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Famazonaws.com%2Frds-data" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with AWS RDS Data API.

Execute a single SQL statement with named parameters via Execute against an Aurora cluster

Run a parameterized statement across many parameter sets in one call using BatchExecute

Open a transaction with BeginTransaction and thread the transactionId through subsequent calls

Commit or roll back a transaction by transactionId with CommitTransaction or RollbackTransaction

Authenticate via a Secrets Manager secret ARN that holds the database credentials, not raw passwords

Return strongly-typed columnMetadata and records for SELECT statements without manual deserialization

Use Cases

Patterns agents use AWS RDS Data API for, with concrete tasks.

★ Serverless SQL from Lambda

Call SQL from AWS Lambda or any HTTPS-capable client without VPC attachment, NAT, or a connection pool. ExecuteStatement (POST /Execute) takes resourceArn, secretArn, database, sql, and named parameters and returns columnMetadata plus records. The credentials live in Secrets Manager, so the function only needs IAM permissions for rds-data:ExecuteStatement and secretsmanager:GetSecretValue.

Call POST /Execute with resourceArn of the Aurora cluster, secretArn of the credentials secret, database 'app', sql 'SELECT id,email FROM users WHERE id = :id', and parameters [{name:'id',value:{longValue:42}}]

Batch Inserts and Imports

Bulk-load data without paying the per-statement HTTP overhead by using BatchExecute. The API accepts a single sql template and an array of parameterSets and runs the same statement once per set inside one call. Useful for syncing webhook payloads, ETL row inserts, or migration top-ups into Aurora Serverless.

Call POST /BatchExecute with sql 'INSERT INTO events(id, payload) VALUES(:id, :payload)' and parameterSets containing one entry per event

Multi-Statement Transactions

Run several SQL statements atomically over HTTPS by opening a transaction with BeginTransaction, threading the returned transactionId into each Execute call, and committing or rolling back at the end. Common for handling money movement, idempotent upserts, or multi-table writes from a stateless service.

Call POST /BeginTransaction to obtain transactionId, run two Execute calls with that transactionId for INSERT and UPDATE, then POST /CommitTransaction with the same transactionId

AI Agent Database Tool via Jentic

An agent that needs to read or write SQL data uses Jentic to discover the RDS Data API, load Execute, and run parameterized statements against Aurora. Jentic stores the AWS access key in its vault and signs requests with SigV4; the database credentials themselves stay in Secrets Manager and are referenced by ARN, so secrets never enter the agent context.

Use Jentic to search 'execute sql against aurora serverless', load Execute, and execute it with resourceArn, secretArn, database, and parameterized sql

Key Endpoints

6 endpoints — jentic publishes the only available openapi specification for the aws rds data api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/Execute

Execute a single SQL statement with named parameters

POST

/BatchExecute

Run a parameterized statement across many parameter sets

POST

/BeginTransaction

Open a transaction and return a transactionId

POST

/CommitTransaction

Commit an open transaction

POST

/RollbackTransaction

Roll back an open transaction

POST

/ExecuteSql

Legacy SQL execution endpoint

POST

/Execute

Execute a single SQL statement with named parameters

POST

/BatchExecute

Run a parameterized statement across many parameter sets

POST

/BeginTransaction

Open a transaction and return a transactionId

POST

/CommitTransaction

Commit an open transaction

POST

/RollbackTransaction

Roll back an open transaction

POST

/ExecuteSql

Legacy SQL execution endpoint

Jentic AI Readiness Score

This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.

A

AWS RDS DataService

- AI-Aware (B-)
62/100
100
Foundational Compliance
63
Developer Experience & Jentic Compatibility
39
AI-Readiness & Agent Experience
94
Agent Usability
50
Security
100
AI Discoverability
Powered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
100

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A+Signals: 4
98%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

100%

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

100%

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

63

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: B-Signals: 4
0%

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

50%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

100%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

39

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: FSignals: 4
57%

Description Coverage

Coverage of descriptions across API elements.

0%

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

0%

Summary Coverage

Coverage of summaries across operations/tags/info.

94

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1
94%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

50

Security

Trust, risk posture, and security compliance.

Grade: C-Signals: 1
50%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

100

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: A+Signals: 1
100%

Descriptive Richness

Clarity and depth of descriptions across API elements.

View full reportHow the score is calculatedMore about the dimensions

Score it yourself

Every API in the directory is allowlisted, so you can re-score it with no key required.

Score your own APIScoring CLI agent skill
npx @jentic/api-scorecard-cli score <openapi-url>

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring the RDS Data API by hand means computing SigV4 HMAC signatures per request, routing to the regional rds-data host, referencing a database secret by ARN in Secrets Manager, and typing SQL parameters correctly yourself. Through Jentic you install once, import AWS RDS Data API from the API Directory, store your AWS access keys once, and your agent calls it with signing handled per request.

Permission scoping

The cluster ARN, secret ARN, and SQL travel in the request body rather than the URL path, so you limit the agent to the operations it needs, such as Execute and BatchExecute for statement execution. Transaction-control operations like CommitTransaction and RollbackTransaction are included only when you grant them.

Credential isolation

Your AWS access keys are stored once, encrypted, by your own Jentic One instance and used to produce a SigV4 signature per request, while the database credential stays in Secrets Manager referenced by ARN. Neither the AWS secret access key nor the database password enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'run SQL against an Aurora Serverless cluster', and Jentic returns Execute with its parameter schema for resourceArn, secretArn, database, sql, and parameters so the agent calls the right endpoint directly.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Amazon Redshift Data API

→

Same HTTPS-SQL pattern as RDS Data API but targeted at Redshift clusters and serverless workgroups

Use Redshift Data API for analytical queries against Redshift; use RDS Data API for transactional Aurora Serverless and Aurora DSQL workloads.

Alternative

Amazon QLDB Session

→

QLDB Session runs PartiQL on append-only ledgers; RDS Data API runs SQL on Aurora

Use QLDB Session when the application requires an immutable, cryptographically verifiable ledger; use RDS Data API for general-purpose relational data.

Complementary

AWS Performance Insights

→

Diagnose slow SQL surfaced by RDS Data API calls using Performance Insights load attribution

Use Performance Insights when the agent needs to attribute load on the underlying Aurora cluster; the Data API does not return per-query timings beyond response duration.

FAQs

Specific to using AWS RDS Data API through Jentic.

Why is there no official OpenAPI spec for the AWS RDS Data API?

AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call the AWS RDS Data API via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.

What authentication does the RDS Data API use?

The API uses AWS SigV4 HMAC request signing for the HTTPS call, plus a Secrets Manager secretArn parameter that holds the database username and password. Through Jentic, AWS credentials are stored in the vault and SigV4 signatures are produced per request.

Which databases does the RDS Data API support?

The Data API supports Aurora Serverless v1 and v2 for PostgreSQL and MySQL, and Aurora DSQL. It does not work against provisioned Aurora clusters running classic engines or other RDS engines like Oracle, SQL Server, or MariaDB.

Can I run multi-statement transactions?

Yes. POST /BeginTransaction returns a transactionId; pass that transactionId into each POST /Execute call and finish with POST /CommitTransaction or POST /RollbackTransaction. Transactions time out after a few minutes of inactivity.

What are the rate limits for the RDS Data API?

The Data API enforces per-account, per-region quotas on simultaneous connections and result-set size (around 1 MB). Throttled requests return BadRequestException or 429 with a throttling message; back off and retry, and use BatchExecute to reduce per-row request volume.

How do I run a parameterized query through Jentic?

Search Jentic for 'execute sql against aurora serverless', load Execute, and execute it with resourceArn, secretArn, database, sql containing named placeholders, and parameters. Install with pip install jentic; AWS credentials come from your Jentic One instance.

Can I limit what my agent is allowed to do with the AWS RDS Data API?

Yes. Because Jentic One is self-hosted, you decide which of the six operations your agent may call, so you can grant only Execute and BatchExecute for statement execution and withhold everything else. Transaction-control operations such as BeginTransaction, CommitTransaction, and RollbackTransaction are available to the agent only when you choose to include them. The cluster ARN, secret ARN, and SQL all travel in the request body under rules you set, keeping the agent scoped to the exact access it needs.

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View OpenAPI Document