DBMS > Greenplum vs. Postgres-XL vs. Rockset vs. Snowflake

System Properties Comparison Greenplum vs. Postgres-XL vs. Rockset 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.

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

docs.greenplum.org

www.postgres-xl.org/documentation

docs.rockset.com

docs.snowflake.net/manuals/index.html

Developer

Pivotal Software Inc.

Rockset

Snowflake Computing Inc.

Initial release

2005

2014

since 2012, originally named StormDB

2019

2014

Current release

7.0.0, September 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Mozilla public license

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

Linux
macOS

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

dynamic 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

since Version 4.2

yes

XML type, but no XML query functionality

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

distributed, parallel query execution

Read-only SQL queries, including JOINs

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

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

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
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

horizontal partitioning

Automatic sharding

yes

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

Eventual Consistency

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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

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