DBMS > atoti vs. FatDB vs. RDF4J vs. Transwarp KunDB

System Properties Comparison atoti vs. FatDB vs. RDF4J vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Object oriented DBMS

Document store
Key-value store

RDF store

Relational DBMS

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.04
Rank	#362	Overall
	#154	Relational DBMS

Website

atoti.io

rdf4j.org

www.transwarp.cn/en/product/kundb

Technical documentation

docs.atoti.io

rdf4j.org/documentation

Developer

ActiveViam

FatCloud

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

Transwarp

Initial release

2012

2004

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

Via inetgration in SQL Server

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java
PHP
Python

Server-side scripts

Stored procedures

Python

yes

via applications

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

Can implement custom security layer via applications

yes

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Recent citations in the news

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