DBMS > Amazon Aurora vs. JanusGraph vs. MySQL vs. Oracle Coherence vs. Teradata

System Properties Comparison Amazon Aurora vs. JanusGraph vs. MySQL vs. Oracle Coherence vs. Teradata

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Widely used open source RDBMS

Oracles in-memory data grid solution

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

aws.amazon.com/rds/aurora

janusgraph.org

www.mysql.com

www.oracle.com/java/coherence

www.teradata.com

Technical documentation

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

docs.janusgraph.org

dev.mysql.com/doc

docs.oracle.com/en/middleware/standalone/coherence

docs.teradata.com

Developer

Amazon

Linux Foundation; originally developed as Titan by Aurelius

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Teradata

Initial release

2015

2017

1995

2007

1984

Current release

0.6.3, February 2023

8.4.0, April 2024

14.1, August 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Java

Server operating systems

hosted

Linux
OS X
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted
Linux

Data scheme

yes

schema-free

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

yes

SQL 2016 + extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
Proprietary native API

JCache
JPA
RESTful HTTP API

.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

Clojure
Java
Python

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

.Net
C++
Java

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

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

configurable

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

optionally

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

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

no user groups or roles

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

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