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Home/Categories/Databases & Storage/TDengine
icon of TDengine

TDengine

Open source alternative to InfluxDB Cloud, Timescale Cloud and Datadog

  • 25.2K stars
  • AGPL-3.0
  • Active this week
  • Last commit 3 days ago

Last verified Oct 20, 2026

Monitor industrial time-series data with a self-hosted TSDB built for IoT ingestion, SQL analytics, and high-volume edge-to-cloud workloads.

Visit websiteGitHub25.2K starsDeploy on Hostinger
image of TDengine
TL;DR

TDengine is an AGPL-3.0 time-series database built for industrial IoT, telemetry, and high-volume sensor workloads. It replaces managed time-series stacks such as InfluxDB Cloud or Timescale Cloud when teams need local control, SQL access, and ingestion paths for operational data. It fits industrial teams more than general app developers looking for a simple relational database.

Read the full breakdownHide the full breakdownWho it is for, how it works, trade-offs and the FAQ
who it's for

Who TDengine is for#

Industrial teams storing sensor telemetry

TDengine fits plants, device fleets, and monitoring systems that ingest large volumes of time-stamped measurements.

Skip if:

Your data is mostly business transactions or document records; PostgreSQL or another general database is a better default.

Edge operators with data residency constraints

Self-managed deployments help keep operational metrics close to machines and local networks.

Skip if:

You prefer a fully managed SaaS time-series database and do not have local data-control requirements.

the problem

The problem it solves#

Industrial telemetry creates data patterns that general databases handle poorly: millions of time-stamped points, many devices, retention rules, downsampling, and queries over recent windows. Teams often end up stitching together brokers, ETL jobs, and analytics databases before they can answer basic operational questions.

Managed time-series services reduce operations work, but they can introduce data residency concerns and recurring cost surprises when sensor volume grows. Plants, utilities, and edge deployments often need time-series storage close to the equipment, not only in a cloud account.

how TDengine solves it

How it solves it#

Time-series database engine

TDengine centers ingestion, storage, and query behavior around timestamped metrics rather than treating telemetry as ordinary relational rows.

Industrial IoT positioning

The project documents use cases around sensors, connected devices, and operational monitoring, which makes it more specialized than a generic analytics database.

SQL-oriented access

Teams can query time-series data through SQL-style interfaces instead of forcing every analyst into a custom telemetry query language.

Edge and cloud deployment paths

TDengine supports self-managed deployments for teams that need data close to devices, with commercial cloud options available separately.

strengths · trade-offs

Strengths and trade-offs#

Strengths

  • Purpose-built for telemetry volumeTDengine focuses on high-ingest time-series workloads, which is a clearer fit for sensor fleets than bolting telemetry tables onto a general OLTP database.
  • Open source core for data controlThe AGPL-3.0 repository gives infrastructure teams a self-managed path when operational data cannot leave a site or region.

Trade-offs

  • -Specialized operational surfaceTDengine is not a general PostgreSQL replacement. Teams need time-series expertise and must validate connector support, retention design, and backup procedures for their environment.
  • -AGPL-3.0 obligationsOrganizations modifying and offering the software over a network should review AGPL requirements before embedding TDengine into a commercial service.
versus alternatives

TDengine vs alternatives#

TDengine vs InfluxDB Cloud

TDengine and InfluxDB both target time-series data, but TDengine is especially positioned around industrial IoT and self-managed operational deployments.

CriteriaTDengineInfluxDB Cloud
LicenseAGPL-3.0 repositoryProprietary managed service plus open source components
Self-hostingYesManaged cloud focus
Primary fitIndustrial telemetry and device dataBroad metrics, monitoring, and time-series analytics

TDengine is stronger when industrial deployment control, edge placement, and SQL-style telemetry access matter. InfluxDB Cloud is still worth considering when the team wants a managed service and broad ecosystem support over running database infrastructure.

tech stack · detected from GitHub

What it's built on#

Languages
CC++Go
Frameworks
Vue
Databases
MySQLPostgreSQL
frequently asked

FAQ#

What is TDengine used for?

TDengine is used for time-series data, especially industrial IoT telemetry, sensor measurements, device monitoring, and operational analytics.

Is TDengine open source?

Yes. TDengine is available under the AGPL-3.0 license, with commercial offerings available from TDengine's vendor.

Is TDengine a PostgreSQL alternative?

TDengine is not a general relational database replacement. It is a specialized time-series database for timestamped telemetry workloads.

also worth a look

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Hostinger

Run TDengine on your own server

Self-host TDengine on a Hostinger VPS.

Deploy on Hostinger

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