DBMS > DataFS vs. Datomic vs. Netezza

System Properties Comparison DataFS vs. Datomic vs. Netezza

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Website

newdatabase.com

www.datomic.com

www.ibm.com/products/netezza

Technical documentation

dev.mobiland.com/Overview.xsp

docs.datomic.com

Developer

Mobiland AG

Cognitect

IBM

Initial release

2018

2012

2000

Current release

1.1.263, October 2022

1.0.7180, July 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

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

Java, Clojure

Server operating systems

Windows

All OS with a Java VM

Linux

included in appliance

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C#
C++
VB.Net

Clojure
Java

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

no, except callback-events from server when changes happened

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

Windows-Profile

Users with fine-grained authorization concept

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More resources

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