DBMS > EsgynDB vs. RDFox vs. SWC-DB

System Properties Comparison EsgynDB vs. RDFox vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

High performance knowledge graph and semantic reasoning engine

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Graph DBMS
RDF store

Wide column store

Secondary database models

Relational DBMS

Time Series DBMS

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

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.24
Rank	#309	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Website

www.esgyn.cn

www.oxfordsemantic.tech

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.oxfordsemantic.tech

Developer

Esgyn

Oxford Semantic Technologies

Alex Kashirin

Initial release

2015

2017

2020

Current release

6.0, Septermber 2022

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

C++

Server operating systems

Linux

Linux
macOS
Windows

Linux

Data scheme

yes

RDF schemas

schema-free

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

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API
SPARQL 1.1

Proprietary protocol
Thrift

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
Java

C++

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

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 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

Roles, resources, and access types

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