DBMS > FatDB vs. GridGain vs. mSQL vs. Netezza

System Properties Comparison FatDB vs. GridGain vs. mSQL vs. Netezza

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

GridGain is an in-memory computing platform, built on Apache Ignite

mSQL (Mini SQL) is a simple and lightweight RDBMS

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store
Key-value store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Website

www.gridgain.com

hughestech.com.au/products/msql

www.ibm.com/products/netezza

Technical documentation

www.gridgain.com/docs/index.html

Developer

FatCloud

GridGain Systems, Inc.

Hughes Technologies

IBM

Initial release

2012

2007

1994

2000

Current release

GridGain 8.5.1

4.4, October 2021

License

Commercial or Open Source

commercial

commercial, open source

commercial

free licenses can be provided

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net, Python, REST, SQL

Server operating systems

Windows

Linux
OS X
Solaris
Windows
z/OS

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

included in appliance

Data scheme

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

SQL

Support of SQL

Via inetgration in SQL Server

ANSI-99 for query and DML statements, subset of DDL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC

JDBC
ODBC
OLE DB

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

via applications

yes (compute grid and cache interceptors can be used instead)

yes

Triggers

yes

via applications

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes (replicated cache)

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Can implement custom security layer via applications

Role-based access control
Security Hooks for custom implementations

Users with fine-grained authorization concept

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