DBMS > Oracle Berkeley DB vs. Realm vs. TerminusDB

System Properties Comparison Oracle Berkeley DB vs. Realm vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

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

realm.io

terminusdb.com

Technical documentation

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

realm.io/docs

terminusdb.github.io/terminusdb/#

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Realm, acquired by MongoDB in May 2019

DataChemist Ltd.

Initial release

1994

2014

2018

Current release

18.1.40, May 2020

11.0.0, January 2023

License

Commercial or Open Source

Open Source

commercial license available

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

Prolog, Rust

Server operating systems

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

SQL-like query language (WOQL)

APIs and other access methods

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.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

JavaScript
Python

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

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

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

User concepts

Access control

yes

Role-based access control

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