Databases 15 min read

Introduction to Apache IoTDB: Features, Architecture, Installation, and Basic Usage

This article introduces Apache IoTDB, a high‑performance time‑series database for IoT, covering its key features, overall architecture, installation procedures, command‑line operations, and JDBC usage with example code to help newcomers quickly start storing and querying sensor data.

Big Data Technology & Architecture
Big Data Technology & Architecture
Big Data Technology & Architecture
Introduction to Apache IoTDB: Features, Architecture, Installation, and Basic Usage

Apache IoTDB, an Apache top‑level project announced on September 23, 2020, is an integrated IoT time‑series database that offers lightweight architecture, high performance, and deep integration with Hadoop, Spark, and Flink, making it suitable for massive industrial IoT data storage and analysis.

The system provides unified data collection, storage, and analysis services, supports high‑throughput read/write for millions of devices, efficient fuzzy‑search directory structures, rich query semantics, low hardware cost, flexible deployment options, and tight integration with open‑source ecosystems such as Grafana.

IoTDB’s overall architecture consists of multiple components (data collection, write, storage, query, visualization, and analysis) that together form the IoTDB suite, while the core time‑series engine is referred to simply as IoTDB.

Typical deployment involves using JDBC to ingest sensor data from devices, optionally writing data to local or HDFS‑based TsFile files, and synchronizing TsFiles to Hadoop or Spark for further processing such as anomaly detection or machine learning.

Installation : Ensure JDK ≥ 1.8 and JAVA_HOME are set, then download the binary package from the official site. Start the server with the nohup sbin/start-server.sh >/dev/null 2>&1 & command (or with custom config). Stop the server using $sbin/stop-server.sh.

CLI usage example :

IoTDB> SET STORAGE GROUP TO root.ln
IoTDB> SHOW STORAGE GROUP
+-----------------------------------+
|                      Storage Group|
+-----------------------------------+
|                            root.ln|
+-----------------------------------+
storage group number = 1

IoTDB> CREATE TIMESERIES root.ln.wf01.wt01.status WITH DATATYPE=BOOLEAN, ENCODING=PLAIN
IoTDB> CREATE TIMESERIES root.ln.wf01.wt01.temperature WITH DATATYPE=FLOAT, ENCODING=RLE

IoTDB> INSERT INTO root.ln.wf01.wt01(timestamp,status) values(100,true);
IoTDB> INSERT INTO root.ln.wf01.wt01(timestamp,status,temperature) values(200,false,20.71);

IoTDB> SELECT status FROM root.ln.wf01.wt01
+-----------------------+------------------------+
|                   Time|root.ln.wf01.wt01.status|
+-----------------------+------------------------+
|1970-01-01T08:00:00.100|                    true|
|1970-01-01T08:00:00.200|                   false|
+-----------------------+------------------------+
Total line number = 2

IoTDB> quit

JDBC integration can be added via Maven dependency

<dependency><groupId>org.apache.iotdb</groupId><artifactId>iotdb-jdbc</artifactId><version>0.10.1</version></dependency>

. A sample Java program demonstrates creating storage groups, time series, batch inserts, and various queries using the standard java.sql API.

Overall, this guide provides a complete walkthrough from understanding IoTDB’s capabilities to installing the system, performing basic CLI operations, and integrating it into Java applications via JDBC.

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SQLJDBCTime Series DatabaseIoTInstallationApache IoTDB
Big Data Technology & Architecture
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Big Data Technology & Architecture

Wang Zhiwu, a big data expert, dedicated to sharing big data technology.

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