DBMS > FatDB vs. Netezza vs. SwayDB

System Properties Comparison FatDB vs. Netezza vs. SwayDB

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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.

Data warehouse and analytics appliance part of IBM PureSystems

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

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

Score	6.55
Rank	#52	Overall
	#32	Relational DBMS

Score	0.00
Rank	#381	Overall
	#61	Key-value stores

Website

www.ibm.com/products/netezza

swaydb.simer.au

Developer

FatCloud

IBM

Simer Plaha

Initial release

2012

2000

2018

License

Commercial or Open Source

commercial

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

Server operating systems

Windows

Linux

included in appliance

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

APIs and other access methods

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

JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

via applications

yes

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic execution of operations

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

Users with fine-grained authorization concept

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More resources

Recent citations in the news

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15 January 2025, IBM

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20 December 2024, IBM

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10 September 2024, Supermarket News

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, Amazon Web Services (AWS)

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23 October 2024, ResearchGate

provided by Google News

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