DBMS > Apache IoTDB vs. Cubrid vs. mSQL vs. ObjectBox vs. OrigoDB

System Properties Comparison Apache IoTDB vs. Cubrid vs. mSQL vs. ObjectBox vs. OrigoDB

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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

mSQL (Mini SQL) is a simple and lightweight RDBMS

Extremely fast embedded database for small devices, IoT and Mobile

A fully ACID in-memory object graph database

Primary database model

Time Series DBMS

Relational DBMS

Object oriented DBMS

Document store
Object oriented DBMS

Secondary database models

Time Series DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

iotdb.apache.org

cubrid.com (korean)
cubrid.org (english)

hughestech.com.au/products/msql

objectbox.io

origodb.com

Technical documentation

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

cubrid.org/manuals

docs.objectbox.io

origodb.com/docs

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

Hughes Technologies

ObjectBox Limited

Robert Friberg et al

Initial release

2018

2008

1994

2017

2009

under the name LiveDB

Current release

1.1.0, April 2023

11.0, January 2021

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

free licenses can be provided

Open Source

Apache License 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++, Java

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Android
iOS
Linux
macOS
Windows

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Proprietary native API

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

.Net

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

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

none

horizontal partitioning

client side managed; servers are not synchronized

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

Source-replica replication

none

online/offline synchronization between client and server

Source-replica replication

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

yes

Role based authorization

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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