DBMS > Fujitsu Enterprise Postgres vs. Postgres-XL vs. Teradata

System Properties Comparison Fujitsu Enterprise Postgres vs. Postgres-XL vs. Teradata

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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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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Trend Chart

Score	0.22
Rank	#304	Overall
	#137	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

www.postgresql.fastware.com

www.postgres-xl.org

www.teradata.com

Technical documentation

www.postgresql.fastware.com/product-manuals

www.postgres-xl.org/documentation

docs.teradata.com

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Teradata

Initial release

2014

since 2012, originally named StormDB

1984

Current release

Fujitsu Enterprise Postgres 14, January 2022

10 R1, October 2018

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla public 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

Server operating systems

Linux
Windows

Linux
macOS

hosted
Linux

Data scheme

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

distributed, parallel query execution

yes

SQL 2016 + extensions

APIs and other access methods

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

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

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

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

horizontal partitioning

Sharding

Hashing

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

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

MVCC

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

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More resources

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