DBMS > Microsoft Azure Table Storage vs. Percona Server for MongoDB vs. RDF4J vs. SwayDB

System Properties Comparison Microsoft Azure Table Storage vs. Percona Server for MongoDB vs. RDF4J vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

A Wide Column Store for rapid development using massive semi-structured datasets

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

azure.microsoft.com/en-us/services/storage/tables

www.percona.com/mongodb/software/percona-server-for-mongodb

rdf4j.org

swaydb.simer.au

Technical documentation

docs.percona.com/percona-distribution-for-mongodb

rdf4j.org/documentation

Developer

Microsoft

Percona

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

Simer Plaha

Initial release

2012

2015

2004

2018

Current release

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

GPL Version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GNU Affero GPL V3.0

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

C++

Java

Scala

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

Data scheme

schema-free

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

APIs and other access methods

RESTful HTTP API

proprietary protocol using JSON

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Java
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

ACID

Isolation support depends on the API used

Atomic execution of operations

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

via In-Memory Engine

yes

User concepts

Access control

Access rights based on private key authentication or shared access signatures

Access rights for users and roles

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