DBMS > Firebase Realtime Database vs. ObjectBox vs. Oracle Berkeley DB vs. SAP SQL Anywhere vs. SQLite

System Properties Comparison Firebase Realtime Database vs. ObjectBox vs. Oracle Berkeley DB vs. SAP SQL Anywhere vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

Widely used in-process key-value store

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Object oriented DBMS
Vector DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

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

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

firebase.google.com/products/realtime-database

github.com/objectbox
objectbox.io

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

www.sap.com/products/technology-platform/sql-anywhere.html

www.sqlite.org

Technical documentation

firebase.google.com/docs/database

docs.objectbox.io

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

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

Developer

Google

acquired by Google 2014

ObjectBox Limited

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SAP

formerly Sybase

Dwayne Richard Hipp

Initial release

2012

2017

1994

1992

2000

Current release

4.0 (May 2024)

18.1.40, May 2020

17, July 2015

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

commercial license available

commercial

Open Source

Public Domain

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

hosted

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

yes

not rigid because of 'dynamic typing' concept.

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

SQL-92 is not fully supported

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
JavaScript
Objective-C

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes, in C/C++, Java, .Net or Perl

Triggers

Callbacks are triggered when data changes

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

User concepts

Access control

yes, based on authentication and database rules

yes

fine grained access rights according to SQL-standard

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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