DBMS > Microsoft Azure Cosmos DB vs. MySQL vs. NuoDB vs. Oracle vs. ToroDB

System Properties Comparison Microsoft Azure Cosmos DB vs. MySQL vs. NuoDB vs. Oracle vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

Globally distributed, horizontally scalable, multi-model database service

Widely used open source RDBMS

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

Widely used RDBMS

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

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	0.99
Rank	#195	Overall
	#92	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

www.mysql.com

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

www.oracle.com/database

github.com/torodb/server

Technical documentation

learn.microsoft.com/azure/cosmos-db

dev.mysql.com/doc

doc.nuodb.com

docs.oracle.com/en/database

Developer

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Dassault Systèmes

originally NuoDB, Inc.

Oracle

8Kdata

Initial release

2014

1995

2013

1980

2016

Current release

8.3.0, January 2024

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

limited edition free

commercial

restricted free version is available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

C++

C and C++

Java

Server operating systems

hosted

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

All OS with a Java 7 VM

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
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
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

Server-side scripts

Stored procedures

JavaScript

yes

proprietary syntax

Java, SQL

PL/SQL

also stored procedures in Java possible

Triggers

JavaScript

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

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

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency
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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

not for MyISAM storage engine

ACID

tunable commit protocol

ACID

isolation level can be parameterized

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'

User concepts

Access control

Access rights can be defined down to the item level

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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