DBMS > LevelDB vs. LokiJS vs. MonetDB vs. RDF4J

System Properties Comparison LevelDB vs. LokiJS vs. MonetDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

In-memory JavaScript DBMS

A relational database management system that stores data in columns

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	0.44
Rank	#256	Overall
	#40	Document stores

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

github.com/google/leveldb

github.com/techfort/LokiJS

www.monetdb.org

rdf4j.org

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

techfort.github.io/LokiJS

www.monetdb.org/Documentation

rdf4j.org/documentation

Developer

Google

MonetDB BV

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2011

2014

2004

Current release

1.23, February 2021

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

Mozilla Public License 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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++

JavaScript

Java

Server operating systems

Illumos
Linux
OS X
Windows

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

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

JavaScript API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript

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

Java
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single collection possible

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

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

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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1 December 2014, Matthias Gelbmann

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