DBMS > FoundationDB vs. Netezza vs. Postgres-XL vs. Trafodion

System Properties Comparison FoundationDB vs. Netezza vs. Postgres-XL vs. Trafodion

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Ordered key-value store. Core features are complimented by layers.

Data warehouse and analytics appliance part of IBM PureSystems

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

github.com/apple/foundationdb

www.ibm.com/products/netezza

www.postgres-xl.org

trafodion.apache.org

Technical documentation

apple.github.io/foundationdb

www.postgres-xl.org/documentation

trafodion.apache.org/documentation.html

Developer

FoundationDB

IBM

Apache Software Foundation, originally developed by HP

Initial release

2013

2000

2014

since 2012, originally named StormDB

2014

Current release

6.2.28, November 2020

10 R1, October 2018

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

Open Source

Apache 2.0

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++

C++, Java

Server operating systems

Linux
OS X
Windows

Linux

included in appliance

Linux
macOS

Linux

Data scheme

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

some layers support typing

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

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

yes

distributed, parallel query execution

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

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
C++
Fortran
Java
Lua
Perl
Python
R

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

in SQL-layer only

yes

user defined functions

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

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.

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

FoundationDB team’s new venture, Antithesis, raises $47M to enhance software testing
13 February 2024, SiliconANGLE News

Antithesis Launches Out Of Stealth To Revolutionize Software Reliability
13 February 2024, PR Newswire

Antithesis raises $47M to launch an automated testing platform for software
13 February 2024, TechCrunch

Apple's FoundationDB takes new Record Layer open source, confirms tech underpins CloudKit
14 January 2019, AppleInsider

Apple Acquires FoundationDB
24 March 2015, WSJ

provided by Google News

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

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

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, azure.microsoft.com

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

provided by Google News

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