DBMS > Amazon Aurora vs. MySQL vs. RavenDB vs. RDF4J vs. Teradata

System Properties Comparison Amazon Aurora vs. MySQL vs. RavenDB vs. RDF4J vs. Teradata

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Widely used open source RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store

RDF store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

aws.amazon.com/rds/aurora

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

dev.mysql.com/doc

ravendb.net/docs

rdf4j.org/documentation

docs.teradata.com

Developer

Amazon

Oracle

since 2010, originally MySQL AB, then Sun

Hibernating Rhinos

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

Teradata

Initial release

2015

1995

2010

2004

1984

Current release

8.4.0, April 2024

5.4, July 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL version 3, commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C and C++

Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Unix
Windows

hosted
Linux

Data scheme

yes

schema-free

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

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (RQL)

yes

SQL 2016 + extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

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

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

Java
PHP
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID, Cluster-wide transaction available

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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