DBMS > GBase vs. LokiJS vs. MonetDB vs. Oracle Berkeley DB vs. Transbase

System Properties Comparison GBase vs. LokiJS vs. MonetDB vs. Oracle Berkeley DB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

In-memory JavaScript DBMS

A relational database management system that stores data in columns

Widely used in-process key-value store

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.gbase.cn

github.com/techfort/LokiJS

www.monetdb.org

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

www.transaction.de/en/products/transbase.html

Technical documentation

techfort.github.io/LokiJS

www.monetdb.org/Documentation

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

www.transaction.de/en/products/transbase/features.html

Developer

General Data Technology Co., Ltd.

MonetDB BV

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Transaction Software GmbH

Initial release

2004

2014

2004

1994

1987

Current release

GBase 8a, GBase 8s, GBase 8c

Dec2023 (11.49), December 2023

18.1.40, May 2020

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

commercial license available

commercial

free development license

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, Python

JavaScript

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

C and C++

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

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

via views

yes

SQL

Support of SQL

Standard with numerous extensions

yes

SQL 2003 with some extensions

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JavaScript API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

JavaScript

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

.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++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

yes, in SQL, C, R

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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