DBMS > Microsoft Azure Table Storage vs. MySQL vs. RDF4J vs. RRDtool vs. SwayDB

System Properties Comparison Microsoft Azure Table Storage vs. MySQL vs. RDF4J vs. RRDtool vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

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

Primary database model

Wide column store

Relational DBMS

Key/Value like access via memcached API

RDF store

Time Series DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	2.14
Rank	#124	Overall
	#10	Time Series DBMS

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Website

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

www.mysql.com

rdf4j.org

oss.oetiker.ch/rrdtool

swaydb.simer.au

Technical documentation

dev.mysql.com/doc

rdf4j.org/documentation

oss.oetiker.ch/rrdtool/doc

Developer

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

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

Tobias Oetiker

Simer Plaha

Initial release

2012

1995

2004

1999

2018

Current release

8.3.0, January 2024

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V2 and FLOSS

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C and C++

Java

Implementations in Java (e.g. RRD4J) and C# available

Scala

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

HP-UX
Linux

Data scheme

schema-free

yes

RDF Schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

in-process shared library
Pipes

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

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.

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

optimistic locking

ACID

not for MyISAM storage engine

ACID

Isolation support depends on the API used

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

by using the rrdcached daemon

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 private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

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