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| # Overview |
| |
| IoTDB Ecosystem Integration Bridges the Full Pipeline of Time-Series Data: |
| - Through data collection, it enables second-level device connectivity. |
| - Via data integration, it constructs cross-cloud pipelines. |
| - Leveraging programming frameworks, it accelerates business logic development. |
| - With computing engines, it accomplishes distributed processing. |
| - Through visualization and SQL development, it implements analytical strategies. |
| - Finally, by interfacing with IoT platforms, it achieves edge-cloud synergy—building a complete intelligent closed loop from the physical world to digital decision-making. |
| |
|  |
| |
| The following documentation will help you quickly and comprehensively understand the usage of various integration tools at each stage: |
| |
| - Data Acquisition |
| - Telegraf [Telegraf Plugin](./Telegraf.md) |
| - Data Integration |
| - NiFi [Apache NiFi](./NiFi-IoTDB.md) |
| - Kafka [Kafka](./Programming-Kafka.md) |
| - Computing Engine |
| - Flink [Flink](./Flink-IoTDB.md) |
| - Spark [Spark](./Spark-IoTDB.md) |
| - Visual Analytics |
| - Zeppelin [Zeppelin](./Zeppelin-IoTDB.md) |
| - Grafana [Grafana](./Grafana-Connector.md) |
| - Grafana Plugin [Grafana Plugin](./Grafana-Plugin.md) |
| - DataEase [DataEase](./DataEase.md) |
| - SQL Development |
| - DBeaver [DBeaver](./DBeaver.md) |
| - IoT Platform |
| - Thingsboard [Thingsboard](./Thingsboard.md) |
