DBMS > MySQL vs. NuoDB vs. Oracle vs. Stardog vs. ToroDB

System Properties Comparison MySQL vs. NuoDB vs. Oracle vs. Stardog vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Widely used open source RDBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Widely used RDBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Graph DBMS
RDF store

Document store

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.mysql.com

www.3ds.com/nuodb-distributed-sql-database

www.oracle.com/database

www.stardog.com

github.com/torodb/server

Technical documentation

dev.mysql.com/doc

doc.nuodb.com

docs.oracle.com/en/database

docs.stardog.com

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Dassault Systèmes

originally NuoDB, Inc.

Oracle

Stardog-Union

8Kdata

Initial release

1995

2013

1980

2010

2016

Current release

8.4.0, April 2024

23c, September 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

limited edition free

commercial

restricted free version is available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C++

C and C++

Java

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
macOS
Windows

All OS with a Java 7 VM

Data scheme

yes

Schemaless in JSON and XML columns

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

with proprietary extensions

yes

with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

Java, SQL

PL/SQL

also stored procedures in Java possible

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

data is dynamically stored/cached on the nodes where it is read/written

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

Multi-source replication
Source-replica replication

Multi-source replication in HA-Cluster

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationships in graphs

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

tunable commit protocol

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

MVCC

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Temporary table

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

Access rights for users and roles

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