DBMS > GBase vs. Netezza vs. Newts vs. Valentina Server vs. VoltDB

System Properties Comparison GBase vs. Netezza vs. Newts vs. Valentina Server vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Data warehouse and analytics appliance part of IBM PureSystems

Time Series DBMS based on Cassandra

Object-relational database and reports server

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

www.gbase.cn

www.ibm.com/products/netezza

opennms.github.io/newts

www.valentina-db.net

www.voltdb.com

Technical documentation

github.com/OpenNMS/newts/wiki

valentina-db.com/docs/dokuwiki/v5/doku.php

docs.voltdb.com

Developer

General Data Technology Co., Ltd.

IBM

OpenNMS Group

Paradigma Software

VoltDB Inc.

Initial release

2004

2000

2014

1999

2010

Current release

GBase 8a, GBase 8s, GBase 8c

5.7.5

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, Python

Java

Java, C++

Server operating systems

Linux

included in appliance

Linux
OS X
Windows

Linux
OS X

for development

Data scheme

yes

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

Standard with numerous extensions

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
OLE DB

HTTP REST
Java API

ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

based on Cassandra

Multi-source replication
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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

yes

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

Price Chopper Chooses IBM Netezza to Analyze Its Business Data
8 September 2024, Supermarket News

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

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

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A Look at Valentina
18 April 2014, SitePoint

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7 December 2018, H2S Media

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VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

Unveiling Volt Active Data’s game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Aims for Fast Big Data Development
29 January 2015, ADT Magazine

Solutions Review Sits Down with VoltDB CEO David Flower
17 April 2018, Solutions Review

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12 March 2024, Datanami

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