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3. [caching](/develop/cache/): TDengine always saves the last data point in cache, so Redis is not needed for time-series data processing.
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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.
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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.
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6. Visulization
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6. Visualization
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* supports seamless integration with [Grafana](/third-party/grafana/) for visualization.
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* supports seamless integration with Google Data Studio.
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7. Cluster
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* supports [cluster](/deployment/), with the capability of increasing processing power by adding more nodes.
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* supports [cluster](/deployment/) with the capability of increasing processing power by adding more nodes.
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* Supports [deployment on Kubernetes](/deployment/k8s/)
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* upports high availability is via replication and RAFT.
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* supports high availability via replication and RAFT.
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8. Administration
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* provides [monitoring](/operation/monitor) on running instances of TDengine.
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* provides many ways to [import](/operation/import) and [export](/operation/export) data.
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