DBMS > Greenplum vs. Infobright vs. Postgres-XL vs. Teradata

System Properties Comparison Greenplum vs. Infobright vs. Postgres-XL vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

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

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

greenplum.org

ignitetech.com/softwarelibrary/infobrightdb

www.postgres-xl.org

www.teradata.com

Technical documentation

docs.greenplum.org

www.postgres-xl.org/documentation

docs.teradata.com

Developer

Pivotal Software Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Teradata

Initial release

2005

2014

since 2012, originally named StormDB

1984

Current release

7.0.0, September 2023

10 R1, October 2018

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

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

since Version 4.2

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

Knowledge Grid Technology used instead

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

JDBC
ODBC

ADO.NET
JDBC
ODBC

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

C
Java
Perl
Python
R

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
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

yes

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

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

MVCC

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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Recent citations in the news

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
9 September 2019, AWS Blog

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, O'Reilly Media

RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

provided by Google News

Ignite Buys Database Vendor Infobright
2 May 2017, Datanami

provided by Google News

Principal Financial Group Inc. Reduces Stake in Teradata Co. (NYSE:TDC)
24 May 2024, Defense World

Teradata takes plunge into lakehouse waters, but not everyone is convinced
23 May 2024, The Register

Why Teradata Shares Dropped
24 May 2024, AOL

Director CHOU TIMOTHY C K Sells Shares of Teradata Corp (TDC)
22 May 2024, Yahoo Finance

Teradata AI Unlimited joins Microsoft Fabric in private preview
21 May 2024, Investing.com

provided by Google News

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