DBMS > ObjectBox vs. Oracle Berkeley DB vs. Realm vs. SQLite vs. TDSQL for MySQL

System Properties Comparison ObjectBox vs. Oracle Berkeley DB vs. Realm vs. SQLite vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

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

Widely used in-process key-value store

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

Widely used embeddable, in-process RDBMS

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Object oriented DBMS
Vector DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

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

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

github.com/objectbox
objectbox.io

www.oracle.com/database/technologies/related/berkeleydb.html

realm.io

www.sqlite.org

www.tencentcloud.com/products/dcdb

Technical documentation

docs.objectbox.io

docs.oracle.com/cd/E17076_05/html/index.html

realm.io/docs

www.sqlite.org/docs.html

www.tencentcloud.com/document/product/1042

Developer

ObjectBox Limited

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Realm, acquired by MongoDB in May 2019

Dwayne Richard Hipp

Tencent

Initial release

2017

1994

2014

2000

2013

Current release

4.0 (May 2024)

18.1.40, May 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

commercial license available

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

yes

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, C++ (depending on the Berkeley DB edition)

Server operating systems

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Android
Backend: server-less
iOS
Windows

server-less

hosted

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes, plus "flex" map-like types

yes

not rigid because of 'dynamic typing' concept.

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

SQL-92 is not fully supported

yes

APIs and other access methods

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC

Supported programming languages

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

only for the SQL API

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

none

Multi-source replication
Source-replica replication

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

User concepts

Access control

yes

Users with fine-grained authorization concept

More information provided by the system vendor

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