DBMS > Netezza vs. PostgreSQL vs. Teradata Aster vs. Yaacomo

System Properties Comparison Netezza vs. PostgreSQL vs. Teradata Aster vs. Yaacomo

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Editorial information provided by DB-Engines

Name

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

Description

Data warehouse and analytics appliance part of IBM PureSystems

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Platform for big data analytics on multistructured data sources and types

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Document store

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

Score	19.00
Rank	#33	Overall
	#20	Relational DBMS

Score	552.23
Rank	#4	Overall
	#4	Relational DBMS

Score	0.00
Rank	#335	Overall
	#139	Relational DBMS

Website

www.ibm.com/products/netezza

www.postgresql.org

yaacomo.com

Technical documentation

www.postgresql.org/docs

Developer

IBM

PostgreSQL Global Development Group

www.postgresql.org/developer

Teradata

Q2WEB GmbH

Initial release

2000

1989

1989: Postgres, 1996: PostgreSQL

2005

2009

Current release

13.1, November 2020

License

Commercial or Open Source

commercial

Open Source

BSD

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.

ScaleGrid for PostgreSQL: Fully managed PostgreSQL hosting on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.

Implementation language

Server operating systems

Linux

included in appliance

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux

Android
Linux
Windows

Data scheme

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

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

specific XML-type available, but no XML query functionality.

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC
OLE DB

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

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

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

Source-replica replication

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

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

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 with fine-grained authorization concept

fine grained access rights according to SQL-standard

More information provided by the system vendor

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

3rd parties

General SQL Parser: Instantly adding parsing, decoding, analysis and rewrite SQL processing capability to your products.
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Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development.
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ClusterControl: the only management system you’ll ever need to take control of your open source database infrastructure.
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pgDash: In-Depth PostgreSQL Monitoring.
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EDB: Helping organizations get the most from PostgreSQL, Oracle Migration, High Availability, Security
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

PostgreSQL is the DBMS of the Year 2018
2 January 2019, Paul Andlinger, Matthias Gelbmann

PostgreSQL is the DBMS of the Year 2017
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