DBMS > ObjectBox vs. Realm vs. SQLite vs. Tarantool vs. Ultipa

System Properties Comparison ObjectBox vs. Realm vs. SQLite vs. Tarantool vs. Ultipa

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

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Object oriented DBMS
Vector DBMS

Document store

Relational DBMS

Document store
Key-value store
Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

with Tarantool/GIS extension

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

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	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Score	0.11
Rank	#338	Overall
	#32	Graph DBMS

Website

github.com/objectbox
objectbox.io

Technical documentation

docs.objectbox.io

realm.io/docs

www.sqlite.org/docs.html

www.tarantool.io/en/doc

www.ultipa.com/document

Developer

ObjectBox Limited

Realm, acquired by MongoDB in May 2019

Dwayne Richard Hipp

Ultipa

Initial release

2017

2014

2000

2008

2019

Current release

4.0 (May 2024)

3.46.1 (13 August 2024), August 2024

2.10.0, May 2022

License

Commercial or Open Source

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Public Domain

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

commercial

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++

Server operating systems

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Android
Backend: server-less
iOS
Windows

server-less

BSD
Linux
macOS

Data scheme

yes

dynamic column types

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes, plus "flex" map-like types

yes

not rigid because of 'dynamic typing' concept.

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

Full-featured ANSI SQL support

APIs and other access methods

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Open binary protocol

RESTful HTTP API

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
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Lua, C and SQL stored procedures

Triggers

yes

Change Listeners

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

In-Memory realm

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

yes

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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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