DBMS > Greenplum vs. Oracle vs. Riak KV vs. Solr

System Properties Comparison Greenplum vs. Oracle vs. Riak KV vs. Solr

Please select another system to include it in the comparison.

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.

Widely used RDBMS

Distributed, fault tolerant key-value store

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Search engine

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Spatial DBMS

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

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

greenplum.org

www.oracle.com/database

solr.apache.org

Technical documentation

docs.greenplum.org

docs.oracle.com/en/database

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

solr.apache.org/resources.html

Developer

Pivotal Software Inc.

Oracle

OpenSource, formerly Basho Technologies

Apache Software Foundation

Initial release

2005

1980

2009

2006

Current release

7.0.0, September 2023

23c, September 2023

3.2.0, December 2022

9.5.0, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

Erlang

Java

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API
Native Erlang Interface

Java API
RESTful HTTP/JSON API

Supported programming languages

C
Java
Perl
Python
R

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Erlang

Java plugins

Triggers

yes

pre-commit hooks and post-commit hooks

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

isolation level can be parameterized

optimistic locking

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, using Riak Security

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.