DBMS > MySQL vs. Netezza vs. NuoDB vs. Solr vs. Teradata

System Properties Comparison MySQL vs. Netezza vs. NuoDB vs. Solr vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

Data warehouse and analytics appliance part of IBM PureSystems

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

A widely used distributed, scalable search engine based on Apache Lucene

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

www.mysql.com

www.ibm.com/products/netezza

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

solr.apache.org

www.teradata.com

Technical documentation

dev.mysql.com/doc

doc.nuodb.com

solr.apache.org/resources.html

docs.teradata.com

Developer

Oracle

since 2010, originally MySQL AB, then Sun

IBM

Dassault Systèmes

originally NuoDB, Inc.

Apache Software Foundation

Teradata

Initial release

1995

2000

2013

2006

1984

Current release

8.4.0, April 2024

9.6.0, April 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

limited edition free

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C++

Java

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Linux

included in appliance

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

hosted
Linux

Data scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

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

SQL

Support of SQL

yes

with proprietary extensions

yes

Solr Parallel SQL Interface

yes

SQL 2016 + extensions

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP/JSON 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

C
C++
Fortran
Java
Lua
Perl
Python
R

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Java, SQL

Java plugins

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

Managed transparently by NuoDB

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

not for MyISAM storage engine

ACID

tunable commit protocol

optimistic locking

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

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept

Standard SQL roles/ privileges, Administrative Users

yes

fine grained access rights according to SQL-standard

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