Industrial IoT / SCADA · API / SDK

InfluxDB HTTP API

InfluxData

Write and query time-series data through HTTP interfaces.

Official documentation Download development spec

INFLUXDB 3 CORE / DEVELOPER FIELD GUIDE

Choose an interface. Define a verifiable result.

Company or project context, ten technical entry points and a practical analysis of every reference.

2026-10-08 · Integration not tested

Company / project overview

Original summary of official company or project statements; use the source for the full original page.

InfluxDB 3 Core · About
Company	InfluxData develops InfluxDB for collecting, storing and analyzing time-series data, including industrial telemetry and observability.
Scope	This guide targets InfluxDB3 Core. Enterprise, cloud, v1 and v2 capabilities must not be assumed interchangeable.

Complete official About page ↗

About reference — TA analysis
Audience	Buyers, partners and product owners shortlisting an AI provider.
Our assessment	Use positioning and company history for initial fit. Obtain project-specific deployment, support and commercial terms separately.

Official sources reviewed. No provider API or inference was run; results are illustrative internal contracts.

Top 10 technical entry points

Ten documented technical entry points selected for implementation decisions, not ten independent SDKs or an official ranking.

Choose by the work you need to complete
Interface	Purpose and audience
01 · Line protocol writesAPI / SDK / developer guide	Write timestamped measurements through v3 or compatibility endpoints.Telemetry ingestion developers
02 · SQL and InfluxQL queriesAPI / SDK / developer guide	Query a database using supported SQL or InfluxQL endpoints.Analytics developers
03 · API authenticationAPI / SDK / developer guide	Select the correct token authentication scheme.Client developers
04 · Token lifecycleAPI / SDK / developer guide	Create, manage and revoke authentication tokens.Database administrators
05 · Database managementAPI / SDK / developer guide	Create/list databases and configure retention.Platform administrators
06 · Table schema managementAPI / SDK / developer guide	Manage table definitions and columns.Schema designers
07 · Distinct Value CacheAPI / SDK / developer guide	Configure caches for distinct column values.Filter UI developers
08 · Last Value CacheAPI / SDK / developer guide	Cache recent field values keyed by selected columns.Latest-state dashboard developers
09 · Processing engine triggersAPI / SDK / developer guide	Configure Python plugin triggers and request handlers.Event-processing developers
10 · v1/v2 compatibility migrationAPI / SDK / developer guide	Map supported legacy client operations to compatibility endpoints.Migration engineers

Reference analysis

Capabilities summarize official documentation. Constraints and proposed tests are our engineering assessment.

API / SDK / developer guide

Line protocol writes

Line protocol writes · TA
Target audience	Telemetry ingestion developers
Documented capability	Write timestamped measurements through v3 or compatibility endpoints.
Input → output	Line protocol, database and precision → write status/errors.
Execution environment	InfluxDB3 Core endpoint and authorized token.
Our decision constraint	v3 partial writes default true; 400 may still have committed valid lines.
Our suggested validation	Count accepted/rejected lines; set precision and partial policy explicitly.

Official reference · Line protocol writes ↗

API / SDK / developer guide

SQL and InfluxQL queries

SQL and InfluxQL queries · TA
Target audience	Analytics developers
Documented capability	Query a database using supported SQL or InfluxQL endpoints.
Input → output	Query, parameters and output format → records.
Execution environment	Database read permission and chosen response parser.
Our decision constraint	Formats and endpoint schemas differ; missing database is not empty data.
Our suggested validation	Verify time bounds, units, nulls and result format.

Official reference · SQL and InfluxQL queries ↗

API / SDK / developer guide

API authentication

API authentication · TA
Target audience	Client developers
Documented capability	Select the correct token authentication scheme.
Input → output	Authorization header → authenticated operation.
Execution environment	Bearer works across endpoints; compatibility schemes have narrower scope.
Our decision constraint	v1 Basic password is an authorized token, not a general account password.
Our suggested validation	Confirm endpoint scheme and avoid exposing tokens in URLs/logs.

Official reference · API authentication ↗

API / SDK / developer guide

Token lifecycle

Token lifecycle · TA
Target audience	Database administrators
Documented capability	Create, manage and revoke authentication tokens.
Input → output	Token management request → token metadata or revocation.
Execution environment	Appropriate administrative authority.
Our decision constraint	Admin tokens grant broad system access.
Our suggested validation	Verify intended scope and expired/revoked denial without storing secrets in reports.

Official reference · Token lifecycle ↗

API / SDK / developer guide

Database management

Database management · TA
Target audience	Platform administrators
Documented capability	Create/list databases and configure retention.
Input → output	Database configuration → persisted database settings.
Execution environment	Core server and management authorization.
Our decision constraint	Retention changes affect available history; removal means infinite retention.
Our suggested validation	Read back database identity and explicit retention policy.

Official reference · Database management ↗

API / SDK / developer guide

Table schema management

Table schema management · TA
Target audience	Schema designers
Documented capability	Manage table definitions and columns.
Input → output	Database/table schema request → schema result.
Execution environment	Target Core version and allowed schema limits.
Our decision constraint	Do not assume Enterprise explicit-schema enforcement exists in Core.
Our suggested validation	Compare field types and tag design with actual sample telemetry.

Official reference · Table schema management ↗

API / SDK / developer guide

Distinct Value Cache

Distinct Value Cache · TA
Target audience	Filter UI developers
Documented capability	Configure caches for distinct column values.
Input → output	Database/table/columns → cache configuration.
Execution environment	Authorized cache-management endpoint.
Our decision constraint	Cached values are not a complete audit of all historical events.
Our suggested validation	Compare expected distinct values and configured cache bounds.

Official reference · Distinct Value Cache ↗

API / SDK / developer guide

Last Value Cache

Last Value Cache · TA
Target audience	Latest-state dashboard developers
Documented capability	Cache recent field values keyed by selected columns.
Input → output	Key/value columns, count and TTL → last-value cache.
Execution environment	Supported Core release and cache configuration.
Our decision constraint	TTL and configured count bound cached visibility.
Our suggested validation	Check key isolation and stale/expired value handling.

Official reference · Last Value Cache ↗

API / SDK / developer guide

Processing engine triggers

Processing engine triggers · TA
Target audience	Event-processing developers
Documented capability	Configure Python plugin triggers and request handlers.
Input → output	Trigger event/request → plugin output or error.
Execution environment	Installed plugin, trigger specification and concurrency settings.
Our decision constraint	Error policy can log, retry or disable; retries need idempotent side effects.
Our suggested validation	Verify trigger execution separately from trigger creation.

Official reference · Processing engine triggers ↗

API / SDK / developer guide

v1/v2 compatibility migration

v1/v2 compatibility migration · TA
Target audience	Migration engineers
Documented capability	Map supported legacy client operations to compatibility endpoints.
Input → output	Legacy workload → reviewed Core endpoint mapping.
Execution environment	Pinned client/server versions and migration validation.
Our decision constraint	Compatibility endpoints do not imply full v1/v2 product parity.
Our suggested validation	Compare writes, query language, authentication and error semantics.

Official reference · v1/v2 compatibility migration ↗

Official documentation

Official documentation · Supporting reference analysis
TA	Developers and technical product owners
Our validation advice	Pin the release and follow the target-specific support requirements before implementation.

Official reference · Official documentation ↗

04 / INPUT · EXPECTED OUTPUT · ACCEPTANCE

Expected results before implementation

Illustrative ingestion/query contract. No database, write, query or plugin was executed; counts and readings are invented.

Illustrative contract · no API call or model execution · not measured provider output

Write and readback

Expected behavior — illustrative, not executed
Input	Two valid synthetic lines with explicit seconds precision.
Expected result	Two accepted; readback matches tags, timestamp and field value.
Acceptance	Accept empty 204 body; prove mapping through readback.

Empty time window

Expected behavior — illustrative, not executed
Input	Valid query against existing table with no samples in range.
Expected result	rows=[]; no invented zero measurements.
Acceptance	Preserve requested time bounds and distinguish missing database errors.

Partial v3 write

Expected behavior — illustrative, not executed
Input	Mixed valid/invalid batch with accept_partial=true.
Expected result	Error with rejected lines; valid lines may already be stored.
Acceptance	Do not treat HTTP400 as rollback; reconcile accepted lines before retry.

Atomic rejection requested

Expected behavior — illustrative, not executed
Input	Mixed batch with v3 accept_partial=false.
Expected result	Whole batch rejected; accepted_lines=0.
Acceptance	Verify zero committed rows for that isolated batch identifier.

Map the expected result to your application

Map your actual runtime response into this proposed application contract. All values are invented examples; no credentials or live execution are included.

Expected output JSON — illustrative, not measured · InfluxDBAPI-expected-results.json

{
  "schema_version": "1.0.0",
  "example": true,
  "provider": "InfluxDB 3 Core",
  "status": "ok",
  "input_id": "sample-001",
  "data": {
    "database": "demo_factory",
    "table": "temperature",
    "timestamp_precision": "s",
    "submitted_lines": 2,
    "accepted_lines": 2,
    "rejected_lines": 0,
    "readback_verified": true,
    "rows": [
      {
        "time": "2026-10-08T00:00:00Z",
        "sensor": "demo-1",
        "temperature_c": 23.5
      }
    ]
  },
  "error": null,
  "verification": "illustrative-only;not-provider-response"
}

Download specification, example and acceptance plan

Engineering handoff — our proposed contract and gates
State semantics	Valid empty results differ from errors. Pending work must not appear successful before completion.
Evidence	Record service and SDK versions, request identity, configuration and response mapping. No execution or performance was measured here.
Acceptance proposal	Agree numerical tolerances and workload targets before testing on representative authorized samples.

Development assessment

Machine trend explorer

Development concept · integration not tested

Provider capabilities above are based on official documentation or repositories. The proposed product, inputs, deliverable and acceptance criteria below are our development assessment.

Small prototype

Test one documented operation with a small real sample after access is confirmed. This is a development judgment, not a delivery estimate.

Proposed inputs: A test device or simulator, a tag map and documented units.
Proposed deliverable: Timestamped device values with freshness, unit and connection state.
Acceptance criterion: Verify scaling and timestamps against the source; a disconnected device must not appear healthy.
Dependencies: A gateway or service account, an equipment schema and access to a test environment.

Development sequence

Confirm access to InfluxDB HTTP API, license and the exact supported version.
Prepare the sample above and implement one documented operation for “Machine trend explorer”.
Normalize the result with source, time and explicit error state; keep the provider response for review.
Run the acceptance criterion before estimating rollout effort or committing a customer deliverable.

How to validate demand

Record product views, documentation clicks, specification downloads and contextual hub clicks. These are event counts, not unique people or completed integrations.

This feasibility assessment uses implementation conditions. No traffic-based rank or delivery-time promise is assigned.

InfluxDB HTTP API

Choose an interface. Define a verifiable result.

Company / project overview

Top 10 technical entry points

Reference analysis

Official documentation

Expected results before implementation

Write and readback

Empty time window

Partial v3 write

Atomic rejection requested

Map the expected result to your application

Machine trend explorer

Development sequence

How to validate demand

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