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| # IoTDB Introduction |
| |
| TimechoDB is a high-performance, cost-efficient, and IoT-native time-series database developed by Timecho. As an enterprise-grade extension of Apache IoTDB, it is designed to tackle the complexities of managing large-scale time-series data in IoT environments. These challenges include high-frequency data sampling, massive data volumes, out-of-order data, extended processing times, diverse analytical demands, and high storage and maintenance costs. |
| |
| TimechoDB enhances Apache IoTDB with superior functionality, optimized performance, enterprise-grade reliability, and an intuitive toolset, enabling industrial users to streamline data operations and unlock deeper insights. |
| |
| - [Quick Start](../QuickStart/QuickStart_timecho.md): Download, Deploy, and Use |
| |
| ## 1. TimechoDB Data Management Solution |
| |
| The Timecho ecosystem provides an integrated **collect-store-use** solution, covering the complete lifecycle of time-series data, from acquisition to analysis. |
| |
|  |
| |
| Key components include: |
| |
| 1. **Time-Series Database (TimechoDB)**: |
| 1. The primary storage and processing engine for time-series data, based on Apache IoTDB. |
| 2. Offers **high compression, advanced** **query** **capabilities, real-time stream processing, high availability, and scalability**. |
| 3. Provides **security features, multi-language APIs, and seamless integration with external systems**. |
| 2. **Time-Series Standard File Format** **(Apache** **TsFile)**: |
| 1. A high-performance storage format originally developed by Timecho’s core contributors. |
| 2. Enables **efficient compression and fast querying**. |
| 3. Powers TimechoDB’s **data collection, storage, and analysis pipeline**, ensuring unified data management |
| 3. **Time-Series AI Engine** **(AINode)**: |
| 1. Integrates **machine learning and deep learning** for time-series analytics. |
| 2. Extracts actionable insights directly from TimechoDB-stored data. |
| 4. **Data Collection Framework**: |
| 1. Supports **various industrial protocols, resumable transfers, and network barrier penetration**. |
| 2. Facilitates **reliable data acquisition in challenging industrial environments**. |
| |
| ## 2. TimechoDB Architecture |
| |
| The diagram below illustrates a common cluster deployment (3 ConfigNodes, 3 DataNodes) of TimechoDB: |
| |
|  |
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| ## 3. Key Features |
| |
| TimechoDB offers the following advantages: |
| |
| **Flexible Deployment:** |
| |
| - Supports one-click cloud deployment, on-premise installation, and seamless terminal-cloud synchronization. |
| - Adapts to hybrid, edge, and cloud-native architectures |
| |
| **Cost-Efficient Storage:** |
| |
| - Utilizes high compression ratio storage, eliminating the need for separate real-time and historical databases. |
| - Supports unified data management across different time horizons. |
| |
| **Hierarchical** **Data** **Organization:** |
| |
| - Mirrors real-world industrial structures through hierarchical measurement point modeling. |
| - Enables directory-based navigation, search, and retrieval. |
| |
| **High-Throughput Read****&****Write:** |
| |
| - Optimized for millions of concurrent device connections. |
| - Handles multi-frequency and out-of-order data ingestion with high efficiency. |
| |
| **Advanced Time-Series Query Semantics** **:** |
| |
| - Features a native time-series computation engine with built-in timestamp alignment. |
| - Provides nearly 100 aggregation and analytical functions, enabling AI-powered time-series insights. |
| |
| **Enterprise-Grade High Availability** **:** |
| |
| - Distributed HA architecture ensures 24/7 real-time database services. |
| - Automated resource balancing when nodes are added, removed, or overheated. |
| - Supports heterogeneous clusters with varying hardware configurations. |
| |
| **Operational Simplicity** **:** |
| |
| - Standard SQL query syntax for ease of use. |
| - Multi-language APIs for flexible development. |
| - Comes with a comprehensive toolset, including an intuitive management console |
| |
| **Robust Ecosystem Integration:** |
| |
| - Seamlessly integrates with big data frameworks (Hadoop, Spark) and visualization tools (Grafana, ThingsBoard, DataEase). |
| - Supports device management for industrial IoT environments. |
| |
| ## 4. Enterprise-level Enhancements |
| |
| TimechoDB extends Apache IoTDB with advanced industrial-grade capabilities, including tiered storage, cloud-edge collaboration, visualization tools, and security upgrades. |
| |
| **Dual-Active Deployment:** |
| |
| - Implements active-active high availability, ensuring continuous operations. |
| - Two independent clusters perform real-time bidirectional synchronization. |
| - Both systems accept external writes and maintain eventual consistency. |
| |
| **Seamless Data Synchronization** **:** |
| |
| - Built-in synchronization module supports real-time and batch data aggregation from field devices to central hubs. |
| - Supports full, partial, and cascading aggregation. |
| - Includes enterprise-ready plugins for cross air-gap transmission, encrypted transmission, and compression. |
| |
| **Tiered** **Storage:** |
| |
| - Dynamically categorizes data into hot, warm, and cold tiers. |
| - Efficiently balances SSD, HDD, and cloud storage utilization. |
| - Automatically optimizes data access speed and storage costs. |
| |
| **Enhanced Security** **:** |
| |
| - Implements whitelist-based access control and audit logging. |
| - Strengthens data governance and risk mitigation. |
| |
| **Feature Comparison**: |
| |
| <table style="text-align: left;"> |
| <tbody> |
| <tr> <th colspan="2">Function</th> |
| <th>Apache IoTDB</th> |
| <th>TimechoDB</th> |
| </tr> |
| <tr> |
| <td rowspan="4">Deployment Mode</td> |
| <td>Stand-Alone Deployment</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Distributed Deployment</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Dual Active Deployment</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Container Deployment</td> |
| <td>Partial support</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td rowspan="13">Database Functionality</td> |
| <td>Sensor Management</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Write Data</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Query Data</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Continuous Query</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Trigger</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>User Defined Function</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Permission Management</td> |
| <td>√</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Data Synchronisation</td> |
| <td>Only file synchronization, no built-in plugins</td> |
| <td>Real time synchronization+file synchronization, enriched with built-in plugins</td> |
| </tr> |
| <tr> |
| <td>Stream Processing</td> |
| <td>Only framework, no built-in plugins</td> |
| <td>Framework+rich built-in plugins</td> |
| </tr> |
| <tr> |
| <td>Tiered Storage</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>View</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>White List</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Audit Log</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td rowspan="3">Supporting Tools</td> |
| <td>Workbench</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Cluster Management Tool</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>System Monitor Tool</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Localization</td> |
| <td>Localization Compatibility Certification</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td rowspan="2">Technical Support</td> |
| <td>Best Practices</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| <tr> |
| <td>Use Training</td> |
| <td>-</td> |
| <td>√</td> |
| </tr> |
| </tbody> |
| </table> |
| |
| ### 4.1 Higher Efficiency and Stability |
| |
| TimechoDB achieves up to 10x performance improvements over Apache IoTDB in mission-critical workloads, and provides rapid fault recovery for industrial environments. |
| |
| ### 4.2 Comprehensive Management Tools |
| |
| TimechoDB simplifies deployment, monitoring, and maintenance through an intuitive toolset: |
| |
| - **Cluster Monitoring Dashboard** |
| - Real-time insights into IoTDB and underlying OS health. |
| - 100+ performance metrics for in-depth monitoring and optimization. |
| - |
| -  |
| - |
| -  |
| - |
| -  |
| - |
| - **Database Console** **:** |
| - Simplifies interaction with an intuitive GUI for metadata management, SQL execution, user permissions, and system configuration. |
| - **Cluster Management Tool** **:** |
| - Provides **one-click operations** for cluster deployment, scaling, start/stop, and configuration updates. |
| -  |
| |
| ### 4.3 Professional Enterprise Technical Services |
| |
| TimechoDB offers **vendor-backed enterprise services** to support industrial-scale deployments: |
| |
| - **On-Site Installation & Training**: Hands-on guidance for fast adoption. |
| - **Expert Consulting & Advisory**: Performance tuning and best practices. |
| - **Emergency Support & Remote Assistance**: Minimized downtime for mission-critical operations. |
| - **Custom Development & Optimization**: Tailored solutions for unique industrial use cases. |
| |
| Compared to Apache IoTDB’s 2-3 month release cycle, TimechoDB delivers faster updates and same-day critical issue resolutions, ensuring production stability. |
| |
| ### 4.4 Ecosystem Compatibility & Compliance |
| |
| imechoDB is self-developed, supports mainstream CPUs & operating systems, and meets industry compliance standards, making it a reliable choice for enterprise IoT deployments. |
