@@ -22,13 +22,13 @@ The major features are listed below:
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
6. 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 [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.
*supports high availability via replication and RAFT.
8. Administration
* provides [monitoring](/operation/monitor) on running instances of TDengine.
* provides many ways to [import](/operation/import) and [export](/operation/export) data.
