DBMS > HugeGraph vs. RDFox vs. Sadas Engine vs. VelocityDB

System Properties Comparison HugeGraph vs. RDFox vs. Sadas Engine vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

High performance knowledge graph and semantic reasoning engine

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS

Graph DBMS
RDF store

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.oxfordsemantic.tech

www.sadasengine.com

velocitydb.com

Technical documentation

hugegraph.apache.org/docs

docs.oxfordsemantic.tech

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

velocitydb.com/UserGuide

Developer

Baidu

Oxford Semantic Technologies

SADAS s.r.l.

VelocityDB Inc

Initial release

2018

2017

2006

2011

Current release

0.9

6.0, Septermber 2022

8.0

7.x

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free trial version available

commercial

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++

Server operating systems

Linux
macOS
Unix

Linux
macOS
Windows

AIX
Linux
Windows

Any that supports .NET

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC
Proprietary protocol

.Net

Supported programming languages

Groovy
Java
Python

C
Java

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

replication via a shared file system

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Users, roles and permissions

Roles, resources, and access types

Access rights for users, groups and roles according to SQL-standard

Based on Windows Authentication

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More resources

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