DBMS > Fujitsu Enterprise Postgres vs. GBase vs. Netezza vs. SiriDB vs. SpaceTime

System Properties Comparison Fujitsu Enterprise Postgres vs. GBase vs. Netezza vs. SiriDB vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

Data warehouse and analytics appliance part of IBM PureSystems

Open Source Time Series DBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS

Time Series DBMS

Spatial DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

www.postgresql.fastware.com

www.gbase.cn

www.ibm.com/products/netezza

siridb.com

www.mireo.com/spacetime

Technical documentation

www.postgresql.fastware.com/product-manuals

docs.siridb.com

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

General Data Technology Co., Ltd.

IBM

Cesbit

Mireo

Initial release

2004

2000

2017

2020

Current release

Fujitsu Enterprise Postgres 14, January 2022

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

commercial

Open Source

MIT License

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

C, Java, Python

C++

Server operating systems

Linux
Windows

Linux

included in appliance

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

Standard with numerous extensions

yes

A subset of ANSI SQL is implemented

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
OLE DB

HTTP API

RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C#
C++
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

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

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

yes

Real-time block device replication (DRBD)

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, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

yes

Users with fine-grained authorization concept

simple rights management via user accounts

yes

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Fujitsu Develops Column-Oriented Data-Processing Engine Enabling Fast, High-Volume Data Analysis in Database ...
26 February 2015, Fujitsu

Expert Insight 202009 KAC
4 September 2023, Fujitsu

Fujitsu recognized as winner of 2023 Microsoft Japan Healthcare & Life Sciences Partner of the Year Award for its ...
28 June 2023, Fujitsu

Latest News
17 September 2020, IBM Newsroom

Primary Data says stop, Hammerspace, Innodisk cooks some SSDs, and Fujitsu goes blockchain
22 May 2018, The Register

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

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

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

Netezza Performance Server
12 August 2020, ibm.com

provided by Google News

Share this page