DBMS > Greenplum vs. Netezza vs. Snowflake vs. Transwarp Hippo

System Properties Comparison Greenplum vs. Netezza vs. Snowflake vs. Transwarp Hippo

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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.

Data warehouse and analytics appliance part of IBM PureSystems

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

greenplum.org

www.ibm.com/products/netezza

www.snowflake.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.greenplum.org

docs.snowflake.net/manuals/index.html

Developer

Pivotal Software Inc.

IBM

Snowflake Computing Inc.

Initial release

2005

2000

2014

2023

Current release

7.0.0, September 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux

included in appliance

hosted

Linux
macOS

Data scheme

yes

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

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

C++
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

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

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

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

Users with fine-grained authorization concept

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

Role based access control and fine grained access rights

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