DBMS > atoti vs. DataFS vs. JaguarDB vs. RDFox

System Properties Comparison atoti vs. DataFS vs. JaguarDB vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Performant, highly scalable DBMS for AI and IoT applications

High performance knowledge graph and semantic reasoning engine

Primary database model

Object oriented DBMS

Key-value store
Vector DBMS

Graph DBMS
RDF store

Secondary database models

Graph DBMS

Relational DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Website

atoti.io

newdatabase.com

www.jaguardb.com

www.oxfordsemantic.tech

Technical documentation

docs.atoti.io

dev.mobiland.com/Overview.xsp

www.jaguardb.com/support.html

docs.oxfordsemantic.tech

Developer

ActiveViam

Mobiland AG

DataJaguar, Inc.

Oxford Semantic Technologies

Initial release

2018

2015

2017

Current release

1.1.263, October 2022

3.3 July 2023

6.0, Septermber 2022

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

GPL V3.0

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++

the server part. Clients available in other languages

C++

Server operating systems

Windows

Linux

Linux
macOS
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

JDBC
ODBC

RESTful HTTP API
SPARQL 1.1

Supported programming languages

.Net
C
C#
C++
VB.Net

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
Java

Server-side scripts

Stored procedures

Python

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

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, multi-version concurrency control (MVCC)

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

Windows-Profile

rights management via user accounts

Roles, resources, and access types

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More resources

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