Training Example: Apache IoTDB – Review the Data, Give Your Score & Compare to the Real AI Evaluation

[H2] Main Features
[H3] High-throughput read and write
Apache IoTDB can support high-speed write access for millions of low-power and intelligently networked devices. It also provides lightning read access for retrieving data.
[H3] Efficient directory structure
Apache IoTDB can efficiently organize complex data structure from IoT devices and large size of timeseries data with fuzzy searching strategy for complex directory of timeseries data.
[H3] Rich query semantics
Apache IoTDB can support time alignment for timeseries data across devices and sensors, computation in timeseries field and abundant aggregation functions in time dimension.
[H3] Low cost on hardware
Apache IoTDB can reach a high compression ratio of disk storage (it costs less than $0.23 to store 1GB of data on hard disk).
[H3] Flexible deployment
Apache IoTDB can provide users one-click installation on the cloud, terminal tool on desktop and the bridge tool between cloud platform and on premise machine (Data Synchronization Tool).
[H3] Intense integration with Open Source Ecosystem
Apache IoTDB can support analysis ecosystems, for example, Hadoop, Spark, Flink and Grafana (visualization tool).
[H2] Scenarios
[H3] Energy & Power
The global energy transition accelerates power sector digitization. Enterprises deploy IoT and time-series databases to build smart energy systems, using real-time analytics for efficiency and security. IoTDB provides high-availability, low-bandwidth solutions to streamline data integration and energy transition.
[H3] AeroSpace
Tech advances propel the digital-intelligent shift in aerospace. Enterprises integrate real-time telemetry and test data through lifecycle data management, ensuring precise monitoring and optimized designs. IoTDB delivers low-bandwidth sync and flexible deployment, delivering reliable data foundations for innovation and sustainable energy integration.
[H3] Transportation
Transportation leverages real-time vehicle data to drive smart scheduling and maintenance in railways/metro systems, ensuring real-time and reliable management for efficiency and cost reduction. IoTDB's time-series data processing with low-latency queries handles data surges and multi-source data flow, building a robust foundation for intelligent transport systems and enabling smarter automation.
[H3] Steel & Metallurgy
The steel industry accelerates digital transformation using industrial IoT platforms for real-time production data analytics, boosting output, quality, and energy efficiency. IoTDB, a high-efficiency time-series database, enables cross-platform deployment with low resource use and seamless system integration via APIs, driving smart factories and industrial productivity growth.
[H3] IoT
IoT enables smart industry operations via mass device connectivity and data analytics, driving efficient real-time scalable data management for monitoring and diagnostics. IoTDB, a native time-series database, supports edge-cloud sync and high-concurrency processing, empowering enterprises to unlock data value and advance IoT solutions.Item 1 of 5

[H1] Quick Start
9/23/24About 3 min
[H1] Quick Start
This document will guide you through methods to get started quickly with IoTDB.
[H2] 1. How to Install and Deploy?
This guide will assist you in quickly installing and deploying IoTDB. You can quickly navigate to the content you need to review through the following document links:Prepare the necessary machine resources: The deployment and operation of IoTDB require consideration of various aspects of machine resource configuration. For specific resource configurations, please refer to Database ResourceComplete system configuration preparations: IoTDB's system configuration involves multiple aspects. For an introduction to key system configurations, please see System RequirementsObtain the installation package: You can obtain the IoTDB installation package on the Apache IoTDB official website.For the specific structure of the installation package, please refer toObtain TimechoDBInstall the database and activate it: Depending on your actual deployment architecture, you can choose from the following tutorials for installation and deployment:Stand-Alone Deployment: Stand-Alone Deployment Distributed(Cluster) Deployment:Distributed(Cluster) Deployment❗️Note: We currently still recommend direct installation and deployment on physical/virtual machines. For Docker deployment, please refer to Docker Deployment
[H2] 2. How to Use IoTDB?
Database Modeling Design: Database modeling is a crucial step in creating a database system, involving the design of data structures and relationships to ensure that the organization of data meets the needs of specific applications. The following documents will help you quickly understand IoTDB's modeling design:Introduction to Time Series Concepts: Navigating Time Series DataIntroduction to Modeling Design:Data Model and TerminologyIntroduction to SQL syntaxSQL syntaxWrite Data: In terms of data writing, IoTDB provides multiple ways to insert real-time data. Please refer to the basic data writing operations for details Write DataQuery Data: IoTDB provides rich data query functions. Please refer to the basic introduction of data query Query DataOther advanced features: In addition to common functions such as writing and querying in databases, IoTDB also supports "Data Synchronisation、Stream Framework、Database Administration " and other functions, specific usage methods can be found in the specific document:Data Synchronisation: Data SynchronisationStream Framework: Stream FrameworkAuthority Management:Authority ManagementAPI: IoTDB provides multiple application programming interfaces (API) for developers to interact with IoTDB in their applications, and currently supports Java Native API、Python Native API、C++ Native API ,For more API, please refer to the official website 【API】 and other chapters
[H2] 3. What other convenient tools are available?
In addition to its rich features, IoTDB also has a comprehensive range of tools in its surrounding system. This document will help you quickly use the peripheral tool system :Benchmark Tool: IoT benchmark is a time series database benchmark testing tool developed based on Java and big data environments, developed and open sourced by the School of Software at Tsinghua University. It supports multiple writing and querying methods, can store test information and results for further query or analysis, and supports integration with Tableau to visualize test results. For specific usage instructions, please refer to: Benchmark ToolData Import Script: For different scenarios, IoTDB provides users with multiple ways to batch import data. For specific usage instructions, please refer to: Data ImportData Export Script: For different scenarios, IoTDB provides users with multiple ways to batch export data. For specific usage instructions, please refer to: Data Export
[H2] 4. Want to Learn More About the Technical Details?
If you are interested in delving deeper into the technical aspects of IoTDB, you can refer to the following documents:Publication: IoTDB features columnar storage, data encoding, pre-calculation, and indexing technologies, along with a SQL-like interface and high-performance data processing capabilities. It also integrates seamlessly with Apache Hadoop, MapReduce, and Apache Spark. For related research papers, please refer to: PublicationEncoding & Compression: IoTDB optimizes storage efficiency for different data types through a variety of encoding and compression techniques. To learn more, please refer to:Encoding & CompressionData Partitioning and Load Balancing: IoTDB has meticulously designed data partitioning strategies and load balancing algorithms based on the characteristics of time series data, enhancing the availability and performance of the cluster. For more information, please refer to: Data Partitioning and Load Balancing
[H2] 5. Encountering problems during use?
If you encounter difficulties during installation or use, you can move to Frequently Asked Questions View in the middle

[H1] Release version
7/10/23About 9 min
[H1] Release version
VersionIoTDB BinariesIoTDB Sourcesrelease notes2.0.8All-in-oneSHA512ASCSourcesSHA512ASCrelease notesAINode linux-aarch64SHA512ASC1.3.7All-in-oneSHA512ASCSourcesSHA512ASCrelease notes0.13.4All-in-oneSHA512ASCSourcesSHA512ASCrelease notesGrafana-connectorSHA512ASCGrafana-pluginSHA512ASCLegacy version are available here: https://archive.apache.org/dist/iotdb/
[H2] Configurations
Recommended OS parametersSet the somaxconn as 65535 to avoid "connection reset" error when the system is under high load.# Linux
> sudo sysctl -w net.core.somaxconn=65535
# FreeBSD or Darwin
> sudo sysctl -w kern.ipc.somaxconn=65535
[H2] About Version 1.0
After we release version 1.0, how to upgrade from v0.13.x to v1.0.x?Version 1.0 has changed the SQL syntax conventions (please refer to the syntax conventions section of the user manual).In order to ensure the stability of UDF-related APIs, in version 1.0, UDF-related APIs are seperated into an independent module and no longer depend on the tsfile package. The implemented UDFs need to rewrite the code, replace TsDataType with Type, and replace org .apache.iotdb.tsfile.utils.Binary with org.apache.iotdb.udf.api.type.Binary, then redo the packaging and loading process.
[H3] Detailed description of Syntax Conventions in version 1.0 that are different from older versions
In previous versions of syntax conventions, we introduced some ambiguity to maintain compatibility. To avoid ambiguity, we have designed new syntax conventions, and this chapter will explain the issues with the old syntax conventions and why we made the change.
[H4] Issues related to identifier
In version 0.13 and earlier, identifiers (including path node names) that are not quoted with backquotes are allowed to be pure numbers(Pure numeric path node names need to be enclosed in backquotes in the SELECT clause), and are allowed to contain some special characters. In version 1.0, identifiers that are not quoted with backquotes are not allowed to be pure numbers and only allowed to contain letters, Chinese characters, and underscores.
[H4] Issues related to node name
In previous versions of syntax conventions, when do you need to add quotation marks to the node name, and the rules for using single and double quotation marks or backquotes are complicated. We have unified usage of quotation marks in the new syntax conventions. For details, please refer to the relevant chapters of this document.
[H5] When to use single and double quotes and backquotes
In previous versions of syntax conventions, path node names were defined as identifiers, but when the path separator . was required in the path node name, single or double quotes were required. This goes against the rule that identifiers are quoted using backquotes.# In the previous syntax convention, if you need to create a time series root.sg.`www.baidu.com`, you need to use the following statement:
create root.sg.'www.baidu.com' with datatype=BOOLEAN, encoding=PLAIN
# The time series created by this statement is actually root.sg.'www.baidu.com', that is, the quotation marks are stored together. The three nodes of the time series are {"root","sg","'www.baidu.com'"}.
# In the query statement, if you want to query the data of the time series, the query statement is as follows:
select 'www.baidu.com' from root.sg;In the 1.0 syntax conventions, special node names are uniformly quoted using backquotes:# In the new syntax convention, if you need to create a time series root.sg.`www.baidu.com`, the syntax is as follows:
create root.sg.`www.baidu.com` with 'datatype' = 'BOOLEAN', 'encoding' = 'PLAIN'
#To query the time series, you can use the following statement:
select `www.baidu.com` from root.sg;
[H5] The issues of using quotation marks inside node names
In previous versions of syntax conventions, when single quotes ' and double quotes " are used in path node names, they need to be escaped with a backslash , and the backslashes will be stored as part of the path node name. Other identifiers do not have this restriction, causing inconsistency.# Create time series root.sg.\"a
create timeseries root.sg.`\"a` with datatype=TEXT,encoding=PLAIN;
# Query time series root.sg.\"a
select `\"a` from root.sg;
+-----------------------------+-----------+
| Time|root.sg.\"a|
+-----------------------------+-----------+
|1970-01-01T08:00:00.004+08:00| test|
+-----------------------------+-----------+In the 1.0 syntax convention, special path node names are uniformly referenced with backquotes. When single and double quotes are used in path node names, there is no need to add backslashes to escape, and backquotes need to be double-written. For details, please refer to the relevant chapters of the new syntax conventions.
[H4] Issues related to session API
[H5] Session API syntax restrictions
In version 0.13, the restrictions on using path nodes in non-SQL interfaces are as follows:The node names in path or path prefix as parameter: The node names which should be escaped by backticks (`) in the SQL statement, and escaping is not required here.The node names enclosed in single or double quotes still need to be enclosed in single or double quotes and must be escaped for JAVA strings.For the checkTimeseriesExists interface, since the IoTDB-SQL interface is called internally, the time-series pathname must be consistent with the SQL syntax conventions and be escaped for JAVA strings.In version 1.0, restrictions on using path nodes in non-SQL interfaces were enhanced:The node names in path or path prefix as parameter: The node names which should be escaped by backticks (`) in the SQL statement, escaping is required here.Code example for syntax convention could be found at: example/session/src/main/java/org/apache/iotdb/SyntaxConventionRelatedExample.java
[H5] Inconsistent handling of string escaping between SQL and Session interfaces
In previous releases, there was an inconsistency between the SQL and Session interfaces when using strings. For example, when using SQL to insert Text type data, the string will be unescaped, but not when using the Session interface, which is inconsistent. In the new syntax convention, we do not unescape the strings. What you store is what will be obtained when querying (for the rules of using single and double quotation marks inside strings, please refer to this document for string literal chapter).The following are examples of inconsistencies in the old syntax conventions:Use Session's insertRecord method to insert data into the time series root.sg.a// session insert
String deviceId = "root.sg";
List<String> measurements = new ArrayList<>();
measurements.add("a");
String[] values = new String[]{"\\\\", "\\t", "\\\"", "\\u96d5"};
for(int i = 0; i <= values.length; i++){
List<String> valueList = new ArrayList<>();
valueList.add(values[i]);
session.insertRecord(deviceId, i + 1, measurements, valueList);
}Query the data of root.sg.a, you can see that there is no unescaping:// query result
+-----------------------------+---------+
| Time|root.sg.a|
+-----------------------------+---------+
|1970-01-01T08:00:00.001+08:00| \\|
|1970-01-01T08:00:00.002+08:00| \t|
|1970-01-01T08:00:00.003+08:00| \"|
|1970-01-01T08:00:00.004+08:00| \u96d5|
+-----------------------------+---------+Instead use SQL to insert data into root.sg.a:# SQL insert
insert into root.sg(time, a) values(1, "\\")
insert into root.sg(time, a) values(2, "\t")
insert into root.sg(time, a) values(3, "\"")
insert into root.sg(time, a) values(4, "\u96d5")Query the data of root.sg.a, you can see that the string is unescaped:// query result
+-----------------------------+---------+
| Time|root.sg.a|
+-----------------------------+---------+
|1970-01-01T08:00:00.001+08:00| \|
|1970-01-01T08:00:00.002+08:00| |
|1970-01-01T08:00:00.003+08:00| "|
|1970-01-01T08:00:00.004+08:00| 雕|
+-----------------------------+---------+
[H2] How to Upgrade
How to upgrade a minor version (e.g., from v0.12.3 to v0.12.5)?versions which have the same major version are compatible.Just download and unzip the new version. Then modify the configuration files to keep consistent with what you set in the old version.stop the old version instance, and start the new one.How to upgrade from v0.12.x to v0.13.x?The data format (i.e., TsFile data) of v0.12.x and v0.13.x are compatible, but the WAL file is incompatible. So, you can follow the steps: Execute SET SYSTEM TO READONLY command in CLI. Stop writing new data.Execute flush command to close all TsFiles.We recommend to back up all data files before upgrading for rolling back.Just download, unzip v0.13.x.zip, and modify conf/iotdb-engine.properties, especially the unchangeable configurations like timestamp precision. Let all the directories point to the data folder set in v0.12.x (or the backup folder). You can also modify other settings if you want.Stop IoTDB v0.12.x instance, and then start v0.13.x.After the steps above, please make sure the iotdb_version in data/system/schema/system.properties file is 0.13.x. If not, please change it to 0.13.x manually.NOTICE: V0.13 changes many settings in conf/iotdb-engine.properties, so do not use v0.12's configuration file directly.In 0.13, the SQL syntax has been changed. The identifiers not enclosed in backquotes can only contain the following characters, otherwise they need to be enclosed in backquotes.[0-9 a-z A-Z _ : @ # $ { }] (letters, digits, some special characters)['\u2E80'..'\u9FFF'] (UNICODE Chinese characters)In 0.13, if the path node name in the SELECT clause consists of pure numbers, it needs to be enclosed in backquotes to distinguish it from the constant in the expression. For example, in the statement "select 123 + `123` from root.sg", the former 123 represents a constant, and the latter `123` will be spliced with root.sg, indicating the path root.sg.`123`.How to upgrade from v0.11.x or v0.10.x to v0.12.x?Upgrading from v0.11 or v0.10 to v0.12 is similar as v0.9 to v0.10. The upgrade tool will rewrite the data files automatically.Stop writing new data.Call flush command using sbin/start-cli.sh in original version to close all TsFiles.We recommend to backup the data file (also the wal files and mlog.txt) before upgrading for rolling back.Just download, unzip v0.12.x.zip, and modify conf/iotdb-engine.proeprties to let all the directories point to the folders set in previous version (or the backup folder). You can also modify other settings if you want. Any other config changes in v0.11 should be moved to v0.12.Stop IoTDB v0.11 or v0.10 instance, and start v0.12.x, then the IoTDB will upgrade data file format automatically. It is ok to read and write data when the upgrading process works.After a log All files upgraded successfully! printed, the upgrading completes.NOTICE 1: V0.12 changes many settings in conf/iotdb-engine.properties, so do not use previous configuration file directly.NOTICE 2: V0.12 doesn't support upgrade from v0.9 or lower version, please upgrade to v0.10 first if needed.NOTICE 3: We don't recommend deleting data before the upgrading finished. The deletion will fail if you try to delete data in the database with upgrading files.How to upgrade from v0.10.x to v0.11.x?The data format (i.e., TsFile data) of v0.10.x and v0.11 are compatible, but the WAL file is incompatible. So, you can follow the steps:Stop writing new data.Call flush command using sbin/start-cli.sh in v0.10.x to close all TsFiles.We recommend to backup the wal files and mlog.txt before upgrading for rolling back.Just download, unzip v0.11.x.zip, and modify conf/iotdb-engine.properties to let all the directories point to the data folder set in v0.10.x (or the backup folder). You can also modify other settings if you want.Stop IoTDB v0.10.x instance, and start v0.11.x, then the IoTDB will upgrade data file format automatically.NOTICE: V0.11 changes many settings in conf/iotdb-engine.properties, so do not use v0.10's configuration file directly.How to upgrade from v0.9.x to v0.10.x?Upgrading from v0.9 to v0.10 is more complex than v0.8 to v0.9.Stop writing new data.Call flush command using sbin/start-client.sh in v0.9 to close all TsFiles.We recommend to backup the data file (also the wal files and mlog.txt) before upgrading for rolling back.Just download, unzip v0.10.x.zip, and modify conf/iotdb-engine.proeprties to let all the directories point to the folders set in v0.9.x (or the backup folder). You can also modify other settings if you want.Stop IoTDB v0.9 instance, and start v0.10.x, then the IoTDB will upgrade data file format automatically.How to upgrade from 0.8.x to v0.9.x?We recommend to backup the data file (also the wal files and mlog.txt) before upgrading for rolling back.Just download, unzip v0.9.x.zip, and modify conf/iotdb-engine.properties to let all the directories point to the folders set in v0.8.x (or the backup folder). You can also modify other settings if you want.Stop IoTDB v0.8 instance, and start v0.9.x, then the IoTDB will upgrade data file format automatically.​
[H1] All releases
Find all releases in the Archive repository.
[H1] Verifying Hashes and Signatures
Along with our releases, we also provide sha512 hashes in *.sha512 files and cryptographic signatures in *.asc files. The Apache Software Foundation has an extensive tutorial to verify hashes and signatureswhich you can follow by using any of these release-signing KEYS.

[H1] Quick Start
9/23/24About 3 min
[H1] Quick Start
This document will help you understand how to quickly get started with IoTDB.
[H2] How to install and deploy?
This document will help you quickly install and deploy IoTDB. You can quickly locate the content you need to view through the following document links:Prepare the necessary machine resources:The deployment and operation of IoTDB require consideration of multiple aspects of machine resource configuration. Specific resource allocation can be viewed Database ResourcesComplete system configuration preparation:The system configuration of IoTDB involves multiple aspects, and the key system configuration introductions can be viewed System RequirementsGet installation package:You can visit Apache IoTDB official website Get the IoTDB installation package.The specific installation package structure can be viewed: Obtain IoTDBInstall database: You can choose the following tutorials for installation and deployment based on the actual deployment architecture:Stand-Alone Deployment: Stand-Alone DeploymentDistributed(Cluster) Deployment: Distributed(Cluster) Deployment❗️Attention: Currently, we still recommend installing and deploying directly on physical/virtual machines. If Docker deployment is required, please refer to: Docker Deployment
[H2] How to use it?
Database modeling design: Database modeling is an important step in creating a database system, which involves designing the structure and relationships of data to ensure that the organization of data meets the specific application requirements. The following document will help you quickly understand the modeling design of IoTDB:Introduction to the concept of timeseries: Navigating Time Series DataIntroduction to Modeling Design: Data ModelSQL syntax introduction: Operate MetadataWrite Data: In terms of data writing, IoTDB provides multiple ways to insert real-time data. Please refer to the basic data writing operations for details Write DataQuery Data: IoTDB provides rich data query functions. Please refer to the basic introduction of data query Query DataOther advanced features: In addition to common functions such as writing and querying in databases, IoTDB also supports "Data Synchronisation、Stream Framework、Database Administration " and other functions, specific usage methods can be found in the specific document:Data Synchronisation: Data SynchronisationStream Framework: Stream FrameworkDatabase Administration: Database AdministrationAPI: IoTDB provides multiple application programming interfaces (API) for developers to interact with IoTDB in their applications, and currently supports Java Native API、Python Native API、C++ Native API ,For more API, please refer to the official website 【API】 and other chapters
[H2] What other convenient tools are available?
In addition to its rich features, IoTDB also has a comprehensive range of tools in its surrounding system. This document will help you quickly use the peripheral tool system :Benchmark Tool: IoT benchmark is a time series database benchmark testing tool developed based on Java and big data environments, developed and open sourced by the School of Software at Tsinghua University. It supports multiple writing and querying methods, can store test information and results for further query or analysis, and supports integration with Tableau to visualize test results. For specific usage instructions, please refer to: Benchmark ToolData Import Script: For different scenarios, IoTDB provides users with multiple ways to batch import data. For specific usage instructions, please refer to: Data ImportData Export Script: For different scenarios, IoTDB provides users with multiple ways to batch export data. For specific usage instructions, please refer to: Data Export
[H2] Want to Learn More About the Technical Details?
If you are interested in delving deeper into the technical aspects of IoTDB, you can refer to the following documents:Publication: IoTDB features columnar storage, data encoding, pre-calculation, and indexing technologies, along with a SQL-like interface and high-performance data processing capabilities. It also integrates seamlessly with Apache Hadoop, MapReduce, and Apache Spark. For related research papers, please refer to: PublicationEncoding & Compression: IoTDB optimizes storage efficiency for different data types through a variety of encoding and compression techniques. To learn more, please refer to:Encoding & CompressionData Partitioning and Load Balancing: IoTDB has meticulously designed data partitioning strategies and load balancing algorithms based on the characteristics of time series data, enhancing the availability and performance of the cluster. For more information, please refer to: Data Partitioning and Load Balancing
[H2] Encountering problems during use?
If you encounter difficulties during installation or use, you can move to Frequently Asked Questions View in the middle