DBMS > Apache IoTDB vs. H2 vs. MySQL vs. XTDB

System Properties Comparison Apache IoTDB vs. H2 vs. MySQL vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Widely used open source RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

iotdb.apache.org

www.h2database.com

www.mysql.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

www.h2database.com/html/main.html

dev.mysql.com/doc

www.xtdb.com/docs

Developer

Apache Software Foundation

Thomas Mueller

Oracle

since 2010, originally MySQL AB, then Sun

Juxt Ltd.

Initial release

2018

2005

1995

2019

Current release

1.1.0, April 2023

2.2.220, July 2023

8.4.0, April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

Clojure

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
Native API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
JDBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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