DBMS > Greenplum vs. Impala vs. Snowflake

System Properties Comparison Greenplum vs. Impala vs. Snowflake

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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.

Analytic DBMS for Hadoop

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

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store

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

Score	10.45
Rank	#47	Overall
	#30	Relational DBMS

Score	18.51
Rank	#37	Overall
	#23	Relational DBMS

Score	123.24
Rank	#11	Overall
	#8	Relational DBMS

Website

greenplum.org

www.cloudera.com/products/open-source/apache-hadoop/impala.html

www.snowflake.com

Technical documentation

docs.greenplum.org

docs.cloudera.com/documentation/enterprise/latest/topics/impala.html

docs.snowflake.net/manuals/index.html

Developer

Pivotal Software Inc.

Cloudera

Snowflake Computing Inc.

Initial release

2005

2013

2014

Current release

6.7.1, April 2020

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

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++

Server operating systems

Linux

hosted

Data scheme

yes

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

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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

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