DBMS > Citus vs. ObjectBox vs. Realm vs. SQLite vs. TerminusDB

System Properties Comparison Citus vs. ObjectBox vs. Realm vs. SQLite vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Object oriented DBMS
Vector DBMS

Document store

Relational DBMS

Graph DBMS

Secondary database models

Document store

Time Series DBMS

Document store
RDF store

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

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

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

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

www.citusdata.com

github.com/objectbox
objectbox.io

realm.io

www.sqlite.org

terminusdb.com

Technical documentation

docs.citusdata.com

docs.objectbox.io

realm.io/docs

www.sqlite.org/docs.html

terminusdb.github.io/terminusdb/#

Developer

ObjectBox Limited

Realm, acquired by MongoDB in May 2019

Dwayne Richard Hipp

DataChemist Ltd.

Initial release

2010

2017

2014

2000

2018

Current release

8.1, December 2018

4.0 (May 2024)

3.46.1 (13 August 2024), August 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Public Domain

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

Linux

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Android
Backend: server-less
iOS
Windows

server-less

Linux

Data scheme

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

SQL-92 is not fully supported

SQL-like query language (WOQL)

APIs and other access methods

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

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

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

none

Journaling Streams

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 journaling

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

fine grained access rights according to SQL-standard

yes

Role-based access control

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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