TDengine

TDengine is an industrial data platform built around a distributed time-series database, with tools for collecting and working with operational data. It is strongest for industrial organizations consolidating equipment data and replacing historians or legacy IoT platforms. Its broad connectivity is a real advantage, but the 5,000-tag free tier and costly paid options make the scale of a deployment central to the decision.

Overview

The platform has two main components: TDengine TSDB and TDengine IDMP. TSDB combines time-series storage with caching, stream processing, and data subscription; IDMP extends the offering into ingestion, analytics, modeling, visualization, and AI applications. Built-in ETL cleans and transforms incoming data, making TDengine relevant to collection workflows as well as database workloads.

SQL, retention policies, and horizontal scaling cover important database needs. Ingestion methods include SQL, InfluxDB Line Protocol, OpenTSDB Telnet and JSON protocols, MQTT, OPC UA and OPC DA, Kafka, CSV, PI System, and connections to MySQL, PostgreSQL, Oracle, and MongoDB. This range can help teams bring varied operational and business data into one environment, though organizations should consider the AGPL license governing the open-source TSDB.

TDengine says its architecture can exceed general-purpose databases by more than 10 times in write and query performance while using one tenth the storage cost. Those are vendor performance claims, not a guarantee for every workload; teams should assess them against their own data volumes and query patterns.

Key features

Industrial connectivity and integrations

Connections to OPC, MQTT, and Kafka, paired with built-in ETL, let TDengine handle data before it reaches storage rather than requiring every source to arrive preprocessed. Official integrations include Prometheus, Telegraf, collectd, StatsD, Icinga2, Flink, EMQX, HiveMQ, Grafana, Power BI, Tableau, Superset, Spark, Pandas, DBeaver, qStudio, JetBrains, Node-RED, and Ignition. This breadth suits mixed industrial stacks, although teams should confirm that their particular source and downstream tools fit the supported integration set.

Developer access and deployment

A REST API described by OpenAPI is joined by JDBC, ODBC, Kafka, MQTT, iframe embedding, and an Excel Add-In. Self-hosted installations can run at the edge, in containers or virtual machines, on local servers, or in public, private, and hybrid clouds. For teams that prefer managed infrastructure, TDengine Cloud runs on Amazon Web Services, Microsoft Azure, and Google Cloud Platform. This flexibility accommodates different infrastructure strategies, but it also means buyers must choose between operating the system themselves and paying for managed service or licensed deployments.

Security and support

TDengine says it supports 21 CFR Part 11 technical controls and complies with SOC 2 and ISO 27001/27017 standards. TDengine Cloud encrypts data in transit and at rest and offers role-based access, IP whitelisting, scheduled backups, and cross-cloud or cross-region replication. Standard Support comes with annual plans; Premium Support adds 24×7 coverage for Severity 1 incidents at extra cost. These provisions matter to regulated or operationally sensitive teams, while the premium support charge should be included in budgets that require round-the-clock incident coverage.

Pricing

TDengine uses a freemium model. The Free Tier costs nothing and supports up to 5,000 tags in a self-hosted deployment. It is a practical starting point for evaluation or smaller installations, but the tag ceiling and self-managed infrastructure may not suit a growing or operations-constrained team.

Starter costs $970 a month, billed monthly, for 5,000 tags on fully managed cloud. It preserves the free tier's tag limit while removing self-hosting responsibility, so the premium is principally relevant to teams that value managed deployment. Optional Annual Support costs $3,375 a year for free-tier deployments up to 5,000 tags; it adds support rather than additional tag capacity.

For self-hosting beyond the free option, the 7,500-tag Annual License costs $12,500 a year, while the 7,500-tag Perpetual License costs $31,250, paid once. The annual license suits organizations preferring a recurring term; the perpetual license requires a much larger one-time outlay. Both raise the supported tag count to 7,500, a modest increase over the free tier relative to their price. Premium Support is an additional cost, and teams needing 24×7 Severity 1 coverage should account for it separately.

Platforms

TDengine supports API, Linux, macOS, self-hosted, web, and Windows environments. Its deployment options span edge installations, containers, virtual machines, local servers, and public, private, or hybrid clouds, alongside managed service on AWS, Azure, and Google Cloud Platform.

Who it's for

TDengine is aimed at industrial enterprises and organizations running traditional data historians or legacy industrial IoT platforms. It is a strong fit when a team needs to collect data from varied industrial sources, process it, and make it available to analytics and visualization tools without assembling those capabilities from separate products. Smaller deployments can start on the self-hosted free tier; organizations seeking managed operations or higher capacity should be prepared for substantial paid-plan costs. It is less compelling for teams that only need a small, inexpensive cloud service or do not need industrial connectivity and data handling.

Pros and cons

• Pros: Broad industrial ingestion, built-in ETL, and connections to monitoring, analytics, and visualization tools can consolidate a varied operational data pipeline.
• Pros: Edge, self-hosted, and managed cloud deployment choices give infrastructure teams room to match deployment to their environment.
• Pros: The free self-hosted tier includes clustering and supports up to 5,000 tags, giving teams a meaningful way to begin without a license charge.
• Cons: The free tier is capped at 5,000 tags, and paid self-hosted licenses cost $12,500 a year or $31,250, paid once for 7,500 tags.
• Cons: The open-source TSDB is AGPL-licensed, a consideration for organizations whose deployment or distribution requirements make that license unsuitable.
• Cons: 24×7 Severity 1 Premium Support costs extra, which can increase the operating budget for teams that require it.

Alternatives

InfluxDB is worth considering for teams seeking a time-series database with a free, usage-based cloud entry point or a single-node InfluxDB 3 Core option. ThingsBoard is a better fit when an IoT platform organized around a small device and asset allowance is the priority; its free plan includes 5 devices, 5 assets, and 1M data points per month.

OpenRemote offers a free, full-featured self-hosted IoT platform with community support. Thinger.io is another IoT platform option, with cloud plans described in device and storage terms. AWS IoT SiteWise may suit teams focused on industrial data collection and transfer to the cloud, with a free Data Collection Pack.

Datacake offers a free plan for 5 devices and a paid Hobby plan with up to 25 devices and one year of retention. TagoIO is a possible alternative for smaller projects, with a free plan for 5 devices and 5 dashboards. Ubidots offers a free STEM plan for three devices in non-commercial projects.

For broader comparisons, browse IoT Analytics Software, OLAP Software, and Time-Series Databases.

Verdict

Choose TDengine if you are an industrial organization that needs to unify diverse operational data sources with time-series storage, processing, and integrations, and you can justify the deployment and licensing costs. Its strongest reason to buy is the combination of industrial ingestion breadth and flexible deployment. Look elsewhere if your project is small, price-sensitive, or needs only a lightweight IoT cloud service: the free tier is capped, and the paid options escalate quickly.