DBMS > Netezza vs. OpenMLDB vs. Oracle vs. SWC-DB

System Properties Comparison Netezza vs. OpenMLDB vs. Oracle vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Data warehouse and analytics appliance part of IBM PureSystems

An open-source machine learning database that provides a feature platform for training and inference

Widely used RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Relational 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

Time Series DBMS

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

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.ibm.com/products/netezza

openmldb.ai

www.oracle.com/database

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

openmldb.ai/docs/zh/main

docs.oracle.com/en/database

Developer

IBM

4 Paradigm Inc.

Oracle

Alex Kashirin

Initial release

2000

2020

1980

2020

Current release

2024-2 February 2024

23c, September 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

commercial

restricted free version is available

Open Source

GPL V3

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

C++, Java, Scala

C and C++

C++

Server operating systems

Linux

included in appliance

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

yes

Fixed schema

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC
OLE DB

JDBC
SQLAlchemy

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol
Thrift

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

C++
Go
Java
Python
Scala

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

C++

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

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

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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