TDengine is an open source, high-performance, cloud native [time-series database](https://tdengine.com/tsdb/) optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. Its code, including its cluster feature is open source under GNU AGPL v3.0. Besides the database engine, it provides [caching](/develop/cache), [stream processing](/develop/stream), [data subscription](/develop/tmq) and other functionalities to reduce the system complexity and cost of development and operation.
TDengine is an open source, high-performance, cloud native [time-series database](https://tdengine.com/tsdb/) optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. Its code, including its cluster feature is open source under GNU AGPL v3.0. Besides the database engine, it provides [caching](../develop/cache), [stream processing](../develop/stream), [data subscription](../develop/tmq) and other functionalities to reduce the system complexity and cost of development and operation.
This section introduces the major features, competitive advantages, typical use-cases and benchmarks to help you get a high level overview of TDengine.
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The major features are listed below:
1. Insert data
* supports [using SQL to insert](/develop/insert-data/sql-writing).
* supports [schemaless writing](/reference/schemaless/) just like NoSQL databases. It also supports standard protocols like [InfluxDB LINE](/develop/insert-data/influxdb-line)，[OpenTSDB Telnet](/develop/insert-data/opentsdb-telnet), [OpenTSDB JSON ](/develop/insert-data/opentsdb-json) among others.
* supports seamless integration with third-party tools like [Telegraf](/third-party/telegraf/), [Prometheus](/third-party/prometheus/), [collectd](/third-party/collectd/), [StatsD](/third-party/statsd/), [TCollector](/third-party/tcollector/) and [icinga2/](/third-party/icinga2/), they can write data into TDengine with simple configuration and without a single line of code.
* supports [using SQL to insert](../develop/insert-data/sql-writing).
* supports [schemaless writing](../reference/schemaless/) just like NoSQL databases. It also supports standard protocols like [InfluxDB LINE](../develop/insert-data/influxdb-line)，[OpenTSDB Telnet](../develop/insert-data/opentsdb-telnet), [OpenTSDB JSON ](../develop/insert-data/opentsdb-json) among others.
* supports seamless integration with third-party tools like [Telegraf](../third-party/telegraf/), [Prometheus](../third-party/prometheus/), [collectd](../third-party/collectd/), [StatsD](../third-party/statsd/), [TCollector](../third-party/tcollector/) and [icinga2/](../third-party/icinga2/), they can write data into TDengine with simple configuration and without a single line of code.
2. Query data
* supports standard [SQL](/taos-sql/), including nested query.
* supports [time series specific functions](/taos-sql/function/#time-series-extensions) and [time series specific queries](/taos-sql/distinguished), like downsampling, interpolation, cumulated sum, time weighted average, state window, session window and many others.
* supports [user defined functions](/taos-sql/udf).
3.[Caching](/develop/cache/): TDengine always saves the last data point in cache, so Redis is not needed for time-series data processing.
4.[Stream Processing](/develop/stream/): not only is the continuous query is supported, but TDengine also supports even driven stream processing, so Flink or spark is not needed for time-series daata processing.
5.[Data Dubscription](/develop/tmq/): application can subscribe a table or a set of tables. API is the same as Kafka, but you can specify filter conditions.
* supports standard [SQL](../taos-sql/), including nested query.
* supports [time series specific functions](../taos-sql/function/#time-series-extensions) and [time series specific queries](../taos-sql/distinguished), like downsampling, interpolation, cumulated sum, time weighted average, state window, session window and many others.
* supports [user defined functions](../taos-sql/udf).
3.[Caching](../develop/cache/): TDengine always saves the last data point in cache, so Redis is not needed for time-series data processing.
4.[Stream Processing](../develop/stream/): not only is the continuous query is supported, but TDengine also supports even driven stream processing, so Flink or spark is not needed for time-series daata processing.
5.[Data Dubscription](../develop/tmq/): application can subscribe a table or a set of tables. API is the same as Kafka, but you can specify filter conditions.
6. Visualization
* supports seamless integration with [Grafana](/third-party/grafana/) for visualization.
* supports seamless integration with [Grafana](../third-party/grafana/) for visualization.
* supports seamless integration with Google Data Studio.
7. Cluster
* supports [cluster](/deployment/) with the capability of increasing processing power by adding more nodes.
* supports [deployment on Kubernetes](/deployment/k8s/)
* supports [cluster](../deployment/) with the capability of increasing processing power by adding more nodes.
* supports [deployment on Kubernetes](../deployment/k8s/)
* supports high availability via data replication.
8. Administration
* provides [monitoring](/operation/monitor) on running instances of TDengine.
* provides many ways to [import](/operation/import) and [export](/operation/export) data.
* provides [monitoring](../operation/monitor) on running instances of TDengine.
* provides many ways to [import](../operation/import) and [export](../operation/export) data.
9. Tools
* provides an interactive [command-line interface](/reference/taos-shell) for management, maintenance and ad-hoc queries.
* provides a tool [taosBenchmark](/reference/taosbenchmark/) for testing the performance of TDengine.
* provides an interactive [command-line interface](../reference/taos-shell) for management, maintenance and ad-hoc queries.
* provides a tool [taosBenchmark](../reference/taosbenchmark/) for testing the performance of TDengine.
10. Programming
* provides [connectors](/reference/connector/) for [C/C++](/reference/connector/cpp), [Java](/reference/connector/java), [Python](/reference/connector/python), [Go](/reference/connector/go), [Rust](/reference/connector/rust), [Node.js](/reference/connector/node) and other programming languages.
* provides a [REST API](/reference/rest-api/).
* provides [connectors](../reference/connector/) for [C/C++](../reference/connector/cpp), [Java](../reference/connector/java), [Python](../reference/connector/python), [Go](../reference/connector/go), [Rust](../reference/connector/rust), [Node.js](../reference/connector/node) and other programming languages.
* provides a [REST API](../reference/rest-api/).
For more details on features, please read through the entire documentation.
