DBMS > 4D vs. Atos Standard Common Repository vs. Fujitsu Enterprise Postgres vs. GeoSpock vs. Teradata Aster

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Fujitsu Enterprise Postgres vs. GeoSpock vs. Teradata Aster

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Application development environment with integrated database management system

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Spatial and temporal data processing engine for extreme data scale

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Website

www.4d.com

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.postgresql.fastware.com

geospock.com

Technical documentation

developer.4d.com

www.postgresql.fastware.com/product-manuals

Developer

4D, Inc

Atos Convergence Creators

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

GeoSpock

Teradata

Initial release

1984

2016

2005

Current release

v20, April 2023

1703

Fujitsu Enterprise Postgres 14, January 2022

2.0, September 2019

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Java, Javascript

Server operating systems

OS X
Windows

Linux

Linux
Windows

hosted

Linux

Data scheme

yes

Schema and schema-less with LDAP views

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

optional

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

in Aster File Store

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

yes

close to SQL 92

yes

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

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

JDBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

partitioning by range, list and by hash

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Source-replica replication

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

Users and groups

LDAP bind authentication

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

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

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Recent citations in the news

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

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23 April 2015, The Register

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