DBMS > RDF4J vs. WakandaDB

System Properties Comparison RDF4J vs. WakandaDB

Please select another system to include it in the comparison.

Our visitors often compare RDF4J and WakandaDB with MongoDB, Microsoft Azure Cosmos DB and DuckDB.

Editorial information provided by DB-Engines

Name

Description

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

RDF store

Object oriented DBMS

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

Score	0.90
Rank	#233	Overall
	#9	RDF stores

Score	0.03
Rank	#391	Overall
	#21	Object oriented DBMS

Website

rdf4j.org

wakanda.github.io

Technical documentation

rdf4j.org/documentation

wakanda.github.io/doc

Developer

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

Wakanda SAS

Initial release

2004

2012

Current release

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPLv3, extended commercial license available

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

Java

C++, JavaScript

Server operating systems

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

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.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API

Supported programming languages

Java
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

User concepts

Access control

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Exploring Intelligent Graph and PathQL - DataScienceCentral.com
21 February 2022, Data Science Central

GraphDB Goes Open Source
27 January 2020, iProgrammer

provided by Google News

Job opportunities

Ontologist
Johns Hopkins Applied Physics Laboratory (APL), Laurel, MD

2024 PhD Graduate - Ontologist
Johns Hopkins Applied Physics Laboratory (APL), Laurel, MD

jobs by

Share this page