DBMS > mSQL vs. ObjectBox vs. OceanBase vs. RDF4J

System Properties Comparison mSQL vs. ObjectBox vs. OceanBase vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

mSQL (Mini SQL) is a simple and lightweight RDBMS

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

A distributed, high available RDBMS compatible with Oracle and MySQL

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Object oriented DBMS
Vector DBMS

Relational DBMS

RDF store

Secondary database models

Time Series DBMS

Document store
Wide column store

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

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	1.97
Rank	#119	Overall
	#58	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

hughestech.com.au/products/msql

github.com/objectbox
objectbox.io

en.oceanbase.com

rdf4j.org

Technical documentation

docs.objectbox.io

en.oceanbase.com/docs/oceanbase-database

rdf4j.org/documentation

Developer

Hughes Technologies

ObjectBox Limited

OceanBase

previously Alibaba and Ant Group

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

1994

2017

2010

2004

Current release

4.4, October 2021

4.0 (May 2024)

4.3.0, April 2024

License

Commercial or Open Source

commercial

free licenses can be provided

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C++

Java

Server operating systems

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

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

yes

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

A subset of ANSI SQL is implemented

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

yes

APIs and other access methods

JDBC
ODBC

Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Java
PHP
Python

Server-side scripts

Stored procedures

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Data sync between devices allowing occasional connected databases to work completely offline

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

User concepts

Access control

yes

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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