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TimechoDB Documentation

website·Indexed 33 days ago

https://www.timecho-global.com/docs/

User guides and technical documentation for TimechoDB, a time-series database. Includes quick start guides, SQL manuals for maintenance and set operations, configuration parameters, and details on AI capabilities such as the AINode TimeSeries Large Model. Covers versions including V1.3.x and V2.0.10.x.

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What's inside Timecho

  1. Overview of Flink-TsFile-Connector

    V0.13.x
    The Flink-TsFile-Connector enables Apache Flink to integrate with TsFile external data sources. It allows users to read and write TsFiles via the DataStream and DataSet APIs. Supported capabilities include loading a single TsFile, multiple TsFiles (DataSet API only), or all files within a specific directory from either the local file system or HDFS.

  2. Overview of TimechoDB

    V1.3.x
    TimechoDB is a low-cost, high-performance native temporal database designed for the Internet of Things (IoT). Based on the Apache IoTDB community version, it is a commercial product tailored for industrial big data platforms. It is specifically designed to handle challenges such as large data volumes, high sampling frequencies, unaligned data, and high storage/operation costs associated with time-series data.

  3. Overview of TimechoDB

    TimechoDB is a high-performance, cost-efficient, IoT-native time-series database developed as an enterprise-grade extension of Apache IoTDB. It is specifically designed to handle industrial IoT challenges such as high-frequency sampling, massive data volumes, out-of-order data, and high storage costs. It provides high compression, real-time stream processing, high availability, and scalability.

  4. Overview of Window Functions in IoTDB

    V2.0.10.x-Table
    Window Functions in IoTDB (available from version V 2.0.5) allow calculations on a specific set of rows (a "window") related to the current row. Unlike GROUP BY, window functions do not collapse original data rows, making them ideal for ranking, cumulative sums, and moving averages. They utilize PARTITION BY for grouping, ORDER BY for sorting, and FRAME for defining the calculation range.

  5. Overview of Apache IoTDB for Industrial IoT

    Apache IoTDB is a lightweight, high-performance time-series database specifically designed for Industrial Internet-of-Things (IIoT) applications. It is optimized for massive data volumes, high-throughput ingestion, and low-latency queries. Unlike DevOps-oriented time-series databases, IoTDB does not depend on external RDBMS or NoSQL systems. Key capabilities include high data compression to save disk space/IO, support for time-series exclusive operations (segmentation and subsequence matching), and a tree-structure metadata management module for device naming spaces.

  6. Overview of Telegraf-IoTDB Integration

    Telegraf is an open-source agent developed by InfluxData for collecting, processing, and transmitting metrics. The Telegraf-IoTDB plugin allows monitoring information collected by Telegraf to be output and stored in IoTDB using an IoTDB session for connection and data writing. The plugin is built-in to Telegraf and does not require separate installation.

  7. Overview of Dual-Active Deployment in IoTDB

    V2.0.10.x-Tree
    Dual-Active deployment consists of two independent IoTDB instances (single-node or clusters) that perform real-time mirror synchronization. Both instances can independently receive writes and synchronize that data to the other, ensuring eventual consistency. This setup allows for high availability even with fewer than 3 physical nodes and provides physical isolation via separate power and network rings. This is an Enterprise Edition feature.

  9. Overview of IoTDB MQTT Service

    V0.13.x
    IoTDB supports the MQTT v3.1 (OASIS standard) protocol. It includes a built-in MQTT service that allows remote devices to send messages directly to the IoTDB server. The service listens for published messages and writes the data to storage, where MQTT topics correspond to IoTDB time series.

  12. Overview of IoT Benchmark capabilities

    IoT Benchmark is a cross-platform testing tool (Linux, macOS, Windows) designed for time-series and real-time databases in Industrial Internet of Things (IIoT) scenarios. It generates periodic time-series data to measure throughput, latency, and success rates. Key capabilities include:

    • Support for write-only, query-only, and mixed read/write workloads.
    • Dataset generation and disk persistence for repeated testing and correctness verification.
    • Support for multiple database backends and access methods.
    • Result persistence to files, CSV, MySQL, or IoTDB.
    • Advanced scenarios: out-of-order writes, batch writes, cluster load testing, and dual-write comparisons.