---
sidebar_label: Introduction
title: Introduction to TDengine Cloud Service
---

TDengine Cloud, is the fast, elastic, serverless and cost effective time-series data processing service based on the popular open source time-series database, TDengine. With TDengine Cloud you get the highly optimized and purpose-built for IoT time-series platform, for which TDengine is known. 

This section introduces the major features, competitive advantages and typical use-cases to help you get a high level overview of TDengine cloud service.

## Major Features

The major features are listed below:

1. Data In 
   - Supports [using SQL to insert](../data-in/insert-data).
   - Supports [Telegraf](../data-in/telegraf/).
   - Supports [Prometheus](../data-in/prometheus/).
2. Data Out
   - Supports standard [SQL](../data-out/query-data/), including nested query.
   - Supports exporting data via tool [taosDump](../data-out/taosdump/).
   - Supports writing data to [Prometheus](../data-out/prometheus/).
   - Supports exporting data via [data subscription](../tmq/).
3. Data Explorer: browse through databases and even run SQL queryies once you login.
4. Visualization: 
   - Supports [Grafana](../visual/grafana/)
   - Supports Google data studio (to be released soon)
   - Supports Grafana cloud (to be released soon) 
6. [Stream Processing](../stream/): Not only is the continuous query is supported, but TDengine also supports event driven stream processing, so Flink or Spark is not needed for time-series data processing.
7. [Data Subscription](../tmq/): Application can subscribe a table or a set of tables. API is the same as Kafka, but you can specify filter conditions.
8. Enterprise 
   - Supports backuping data everyday.
   - Supports replicating a database to another region or cloud.
   - Supports VPC peering.
   - Supports Allowed IP list for security.
9. Tools
   - Provides an interactive [Command-line Interface (CLI)](../tools/cli/) for management and ad-hoc queries.
   - Provides a tool [taosBenchmark](../tools/taosbenchmark/) for testing the performance of TDengine.
10. Programming
    - Provides [connectors](../programming/connector/) for Java, Python, Go, Rust, Node.js and other programming languages.
    - Provides a [REST API](../programming/connector/rest-api/).

For more details on features, please read through the entire documentation.

## Competitive Advantages

By making full use of [characteristics of time series data](https://tdengine.com/tsdb/characteristics-of-time-series-data/) and its cloud native design, TDengine Cloud differentiates itself from other time series data cloud services, with the following advantages.

- **Worry Free**: TDengine Cloud is a fast, elastic, serverless purpose built cloud platform for time-series data. It provides worry-free operations with a fully managed cloud service. You pay as you go. 

- **[Simplified Solution](https://tdengine.com/tdengine/simplified-time-series-data-solution/)**: Through built-in caching, stream processing and data subscription features, TDengine provides a simplified solution for time-series data processing. It reduces system design complexity and operation costs significantly.

- **[High-Performance](https://tdengine.com/tdengine/high-performance-time-series-database/)**: It is the only time-series platform to solve the high cardinality issue to support billions of data collection points while outperforming other time-series platforms for data ingestion, querying and data compression.

- **[Ease of Use](https://tdengine.com/tdengine/easy-time-series-data-platform/)**: For administrators, TDengine Cloud provides worry-free operations with a fully managed cloud native solution. For developers, it provides a simple interface, simplified solution and seamless integration with third party tools. For data users, it provides SQL support with powerful time series extensions built for data analytics.

- **[Easy Data Analytics](https://tdengine.com/tdengine/time-series-data-analytics-made-easy/)**: Through super tables, storage and compute separation, data partitioning by time interval, pre-computation and other means, TDengine makes it easy to explore, format, and get access to data in a highly efficient way.

- **Enterprise Ready**: It supports backup, multi-cloud/multi-region database replication, VPC peering and IP whitelisting.

With TDengine cloud, the **total cost of ownership of your time-series data platform can be greatly reduced**.

1. With its built-in caching, stream processing and data subscription, system complexity and operation cost are highly reduced.
2. With SQL support, it can be seamlessly integrated with many third party tools, and learning costs/migration costs are reduced significantly.
3. With the elastic, serverless and fully managed service, the operation and maintenance costs are reduced significantly.

## Technical Ecosystem

This is how TDengine would be situated, in a typical time-series data processing platform:

<figure>

![TDengine Database Technical Ecosystem ](eco_system.webp)

<center><figcaption>Figure 1. TDengine Technical Ecosystem</figcaption></center>
</figure>

On the left-hand side, there are data collection agents like OPC-UA, MQTT, Telegraf and Kafka. On the right-hand side, visualization/BI tools, HMI, Python/R, and IoT Apps can be connected. TDengine itself provides an interactive command-line interface and a web interface for management and maintenance.

## Typical Use Cases

As a high-performance and cloud native time-series database, TDengine's typical use case include but are not limited to IoT, Industrial Internet, Connected Vehicles, IT operation and maintenance, energy, financial markets and other fields. TDengine is a purpose-built database optimized for the characteristics of time series data. As such, it cannot be used to process data from web crawlers, social media, e-commerce, ERP, CRM and so on. More generally TDengine is not a suitable storage engine for non-time-series data. 
