DBMS > MySQL vs. ObjectBox vs. Realm vs. TimescaleDB

System Properties Comparison MySQL vs. ObjectBox vs. Realm vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Key/Value like access via memcached API

Object oriented DBMS
Vector DBMS

Document store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

Relational DBMS

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

www.mysql.com

github.com/objectbox
objectbox.io

realm.io

www.timescale.com

Technical documentation

Developer

Oracle

since 2010, originally MySQL AB, then Sun

ObjectBox Limited

Realm, acquired by MongoDB in May 2019

Timescale

Initial release

1995

2017

2014

2017

Current release

8.4.0, April 2024

4.0 (May 2024)

2.15.0, May 2024

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Apache 2.0

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

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

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

runs within the applications so server-side scripts are unnecessary

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

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

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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21 May 2024

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