DBMS > Greenplum vs. Percona Server for MongoDB vs. Postgres-XL vs. Riak TS

System Properties Comparison Greenplum vs. Percona Server for MongoDB vs. Postgres-XL vs. Riak TS

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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.

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

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	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

greenplum.org

www.percona.com/mongodb/software/percona-server-for-mongodb

www.postgres-xl.org

Technical documentation

docs.greenplum.org

docs.percona.com/percona-distribution-for-mongodb

www.postgres-xl.org/documentation

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Pivotal Software Inc.

Percona

Open Source, formerly Basho Technologies

Initial release

2005

2015

2014

since 2012, originally named StormDB

2015

Current release

7.0.0, September 2023

3.4.10-2.10, November 2017

10 R1, October 2018

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL Version 2

Open Source

Mozilla public license

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

Server operating systems

Linux

Linux
macOS

Linux
OS X

Data scheme

yes

schema-free

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

distributed, parallel query execution

yes, limited

APIs and other access methods

JDBC
ODBC

proprietary protocol using JSON

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

HTTP API
Native Erlang Interface

Supported programming languages

C
Java
Perl
Python
R

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

MVCC

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

via In-Memory Engine

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

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