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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@@ -14,20 +14,20 @@ 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](../data-in/telegraf)，[Prometheus](../data-in/prometheus)，they can write data into TDengine with simple configuration and without a single line of code.
* supports seamless integration with third-party tools like [Telegraf](/third-party/telegraf/)，[Prometheus](/third-party/prometheus/)，they can write data into TDengine with simple configuration and without a single line of code.
2. Query data
* supports standard 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](../taos-sql/database): TDengine always saves the last data point in cache, so Redis is not needed for time-series data processing.
4.[stream processing](../taos-sql/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 subscription](../taos-sql/tmq): application can subscribe a table or a set of tables. API is the same as Kafka, but you can specify filter conditions.
* 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 subscription](/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. Visulization
* supports seamless integration with [Grafana](../visual/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/)
* upports high availability is via replication and RAFT.
8. Administration
* provides [monitoring](/operation/monitor) on running instances of TDengine.
