DBMS > Netezza vs. Snowflake vs. Trafodion

System Properties Comparison Netezza vs. Snowflake vs. Trafodion

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Editorial information provided by DB-Engines

Name

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

Description

Data warehouse and analytics appliance part of IBM PureSystems

Cloud-based data warehousing service for structured and semi-structured data

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

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

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.ibm.com/products/netezza

www.snowflake.com

trafodion.apache.org

Technical documentation

docs.snowflake.net/manuals/index.html

trafodion.apache.org/documentation.html

Developer

IBM

Snowflake Computing Inc.

Apache Software Foundation, originally developed by HP

Initial release

2000

2014

Current release

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Server operating systems

Linux

included in appliance

hosted

Linux

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions

Java Stored Procedures

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

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.

User concepts

Access control

Users with fine-grained authorization concept

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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