DBMS > ObjectBox vs. Realm vs. SQLite vs. TerarkDB vs. TimescaleDB

System Properties Comparison ObjectBox vs. Realm vs. SQLite vs. TerarkDB vs. TimescaleDB

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

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 key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

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

Primary database model

Object oriented DBMS
Vector DBMS

Secondary database models

Time Series DBMS

Relational 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	7.41
Rank	#52	Overall
	#8	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

github.com/objectbox
objectbox.io

realm.io

www.sqlite.org

github.com/bytedance/terarkdb

www.timescale.com

Technical documentation

docs.objectbox.io

realm.io/docs

www.sqlite.org/docs.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

docs.timescale.com

Developer

ObjectBox Limited

Realm, acquired by MongoDB in May 2019

Dwayne Richard Hipp

ByteDance, originally Terark

Timescale

Initial release

2017

2014

2000

2016

2017

Current release

4.0 (May 2024)

3.46.0 (23 May 2024), May 2024

2.15.0, May 2024

License

Commercial or Open Source

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Public Domain

commercial

restricted open source version available

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.

Implementation language

C and C++

C++

Server operating systems

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Android
Backend: server-less
iOS
Windows

server-less

Linux
OS X
Windows

Data scheme

yes

dynamic column types

schema-free

yes

Typing

predefined data types such as float or date

yes, plus "flex" map-like types

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

APIs and other access methods

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

C++ API
Java API

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

Supported programming languages

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

.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++
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

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