DBMS > Alibaba Cloud Table Store vs. Citus vs. DataFS vs. RDF4J vs. Valentina Server

System Properties Comparison Alibaba Cloud Table Store vs. Citus vs. DataFS vs. RDF4J vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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.

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

Object-relational database and reports server

Primary database model

Secondary database models

Document store

Graph DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.alibabacloud.com/product/table-store

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.citusdata.com

dev.mobiland.com/Overview.xsp

rdf4j.org/documentation

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Alibaba

Mobiland AG

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

Paradigma Software

Initial release

2016

2010

2018

2004

1999

Current release

8.1, December 2018

1.1.263, October 2022

5.7.5

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

Linux

Windows

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

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

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

APIs and other access methods

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API
Proprietary client DLL
WinRT client

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ODBC

Supported programming languages

Java
Python

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C#
C++
VB.Net

Java
PHP
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Proprietary Sharding system

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

other methods possible by using 3rd party extensions

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Isolation support depends on the API used

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.

yes

User concepts

Access control

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

Windows-Profile

fine grained access rights according to SQL-standard

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