AWS Amazon Timestream Query
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AI ReadinessAI-Aware (B-)61/100
Agent-ready OpenAPI document · curated by JenticAnalyticsBusiness IntelligenceapiKey13 EndpointsREST
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For Agents
Run SQL queries and manage scheduled queries against Amazon Timestream time-series tables so an agent can read IoT, observability, and DevOps metrics on demand.
Use for: Run a SQL query over the last hour of IoT sensor data, Cancel a long-running Timestream query, Create a scheduled query that aggregates CPU metrics every 5 minutes, List all scheduled queries in my Timestream database
Not supported: Does not handle data ingestion, table or database creation, or real-time alerting - use for running SQL queries and managing scheduled queries on Timestream tables only.
Jentic publishes the only available OpenAPI specification for Amazon Timestream Query, keeping it validated and agent-ready. Amazon Timestream Query is the read-and-schedule API for Amazon Timestream, AWS's serverless time-series database. It runs SQL queries against memory and magnetic stores, prepares parameterised queries, and manages scheduled queries that pre-compute aggregations on a cron-like schedule. The 13 operations cover ad-hoc Query and CancelQuery, the full lifecycle of scheduled queries, endpoint discovery, and resource tagging.
Install Jentic One Beta
Connect the Amazon Timestream Query to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Amazon Timestream Query, 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%2Ftimestream-query" | sh2
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%2Ftimestream-query" | sh
jentic register # connects your agent to your Jentic One instanceJentic 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 Amazon Timestream Query API.
Run ad-hoc SQL queries against Timestream tables via Query with paginated result sets
Cancel an in-flight long-running query with CancelQuery
Create, update, delete, and describe scheduled queries that pre-aggregate time-series data
Trigger scheduled queries on demand via ExecuteScheduledQuery
Prepare parameterised queries with PrepareQuery for repeated execution patterns
Tag and untag scheduled queries for cost allocation and ownership
Discover regional Timestream Query endpoints via DescribeEndpoints
Use Cases
Patterns agents use Amazon Timestream Query API for, with concrete tasks.
★ Ad-Hoc Time-Series Investigation
When an SRE needs to investigate a spike, they run SQL directly against the Timestream Query API: SELECT bin(time, 1m), avg(measure_value::double) FROM iot.sensors WHERE region = 'us-east-1' AND time BETWEEN ago(1h) AND now() GROUP BY 1. The Query operation returns paginated results with QueryStatus showing rows scanned and bytes metered, and CancelQuery aborts the run if it exceeds expectations.
Call Query with QueryString 'SELECT bin(time, 1m) AS minute, avg(measure_value::double) AS avg_temp FROM "iot"."sensors" WHERE time > ago(1h) GROUP BY bin(time, 1m) ORDER BY minute', then page through Rows.
Scheduled Roll-Ups for Dashboards
Pre-aggregate raw metrics into a roll-up table that powers a Grafana or QuickSight dashboard. CreateScheduledQuery accepts a SQL statement, a ScheduleConfiguration cron expression, a TargetConfiguration writing into a destination Timestream table, and a NotificationConfiguration for SNS alerts on failure. The result is a managed materialised view of your time-series data that scales without operating extra infrastructure.
Call CreateScheduledQuery with Name 'cpu-5m-rollup', QueryString aggregating sensors by 5m bins, ScheduleConfiguration.ScheduleExpression 'cron(*/5 * * * ? *)', and TargetConfiguration writing to 'iot.sensors_5m'.
Operational Monitoring and SLA Reporting
Generate SLA reports by combining ad-hoc Query calls (for the report period) with scheduled queries (for daily and weekly roll-ups feeding the report). ListScheduledQueries lets you audit which roll-ups exist; DescribeScheduledQuery returns the SQL and schedule for compliance review. Tag scheduled queries with team and environment to drive cost allocation per business unit.
Call ListScheduledQueries, then for each ScheduledQueryArn call DescribeScheduledQuery and return Name, QueryString, ScheduleExpression, and Tags.
Agent-Driven Time-Series Q&A via Jentic
Embed a natural-language analytics agent that answers operational questions over time-series data. The agent translates the question into SQL, calls Query through Jentic without holding AWS keys, and formats the rows back into a chart or summary. For repeated questions, the agent can promote a successful query into a CreateScheduledQuery so the next answer reads from a pre-aggregated table.
Through Jentic, search for 'run a sql query on amazon timestream', load Query, and execute with QueryString containing the agent's generated SQL.
Key Endpoints
13 endpoints — jentic publishes the only available openapi specification for amazon timestream query, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/#X-Amz-Target=Timestream_20181101.Query
Run a SQL query against Timestream
POST
/#X-Amz-Target=Timestream_20181101.CancelQuery
Cancel an in-flight query
POST
/#X-Amz-Target=Timestream_20181101.CreateScheduledQuery
Create a scheduled query
POST
/#X-Amz-Target=Timestream_20181101.ExecuteScheduledQuery
Run a scheduled query on demand
POST
/#X-Amz-Target=Timestream_20181101.DescribeScheduledQuery
Describe a scheduled query
POST
/#X-Amz-Target=Timestream_20181101.PrepareQuery
Prepare a parameterised query
POST
/#X-Amz-Target=Timestream_20181101.Query
Run a SQL query against Timestream
POST
/#X-Amz-Target=Timestream_20181101.CancelQuery
Cancel an in-flight query
POST
/#X-Amz-Target=Timestream_20181101.CreateScheduledQuery
Create a scheduled query
POST
/#X-Amz-Target=Timestream_20181101.ExecuteScheduledQuery
Run a scheduled query on demand
POST
/#X-Amz-Target=Timestream_20181101.DescribeScheduledQuery
Describe a scheduled query
POST
/#X-Amz-Target=Timestream_20181101.PrepareQuery
Prepare a parameterised query
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
Amazon Timestream Query
- AI-Aware (B-)61/100
99
Foundational Compliance63
Developer Experience & Jentic Compatibility37
AI-Readiness & Agent Experience94
Agent Usability50
Security100
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
99
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: A+Signals: 4
97%
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.
37
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: FSignals: 4
49%
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.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring Amazon Timestream Query by hand means computing SigV4 signatures, handling the query cell endpoint discovery, and routing calls through the X-Amz-Target action header yourself. Through Jentic you install once, import Timestream Query from the API Directory, store the access keys once, and your agent calls it.
Permission scoping
Timestream Query routes its actions through one endpoint by X-Amz-Target rather than resource ids in the path, so scope the agent to the operations it needs, such as Query and DescribeScheduledQuery. You choose the operations it may call, so scheduled-query creation or execution are not included unless you add them.
Credential isolation
Your AWS access keys are stored once, encrypted, by your own Jentic One instance and used to sign each Timestream Query request with SigV4 at execution time. They never enter the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'run a SQL query on Timestream' or 'cancel a running query', and Jentic returns the matching Timestream Query operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Amazon Timestream Query API through Jentic.
Why is there no official OpenAPI spec for Amazon Timestream Query?
AWS does not publish an OpenAPI specification for Amazon Timestream Query; it ships Smithy models and language-specific SDKs instead. Jentic generates and maintains this OpenAPI spec so that AI agents and developers can call Amazon Timestream Query 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 Amazon Timestream Query use?
Timestream Query uses AWS SigV4 with X-Amz-Target identifying the action (e.g. Timestream_20181101.Query). It also requires endpoint discovery: clients call DescribeEndpoints first to learn the cell endpoint to sign against. Through Jentic, your AWS keys are vaulted and Jentic handles SigV4 signing.
Can I run aggregations across billions of points with Timestream Query?
Yes. The Query operation pushes filtering and aggregation down to Timestream's tiered memory and magnetic stores; queries return paginated results with QueryStatus reporting CumulativeBytesMetered. For repeated dashboards, promote the SQL into a scheduled query that writes pre-aggregated rows to a destination table.
What are the rate limits for Timestream Query?
Concurrent query limits are typically 200 per account per region with up to 5GB of data scanned per query and a 60-minute maximum runtime. Scheduled queries have separate per-account quotas. Throttling responses include the standard ThrottlingException.
How do I run a SQL query on Timestream through Jentic?
Search Jentic with 'run a sql query on amazon timestream', load the Query schema, and execute with QueryString set to your SQL and (optionally) MaxRows for pagination. Jentic returns the column metadata and Rows; pass the NextToken back into Query to continue paging.
Can Timestream Query create or drop tables?
No. This API is read-only and scheduled-query-management. Use the separate Timestream Write API (and its CreateDatabase, CreateTable operations) to manage schema, and the Write API's WriteRecords to ingest data.
How are scheduled queries billed?
Scheduled queries are billed by the bytes scanned per execution plus the writes to the target table, the same metering as ad-hoc queries. Tag scheduled queries to attribute the spend back to the owning team.
Can I limit what my agent is allowed to do with the Amazon Timestream Query API?
Yes. Because you run Jentic One yourself, your own rules decide which Timestream Query operations and credentials the agent may use. Timestream Query routes every action through a single endpoint by its X-Amz-Target header rather than resource ids in the path, so you scope the agent to just the operations it needs, such as Query and DescribeScheduledQuery. You choose the operations it may call, so scheduled-query creation with CreateScheduledQuery or manual runs with ExecuteScheduledQuery stay out of reach unless you add them.
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