DBMS > Greenplum vs. Infobright vs. Stardog vs. Warp 10

System Properties Comparison Greenplum vs. Infobright vs. Stardog vs. Warp 10

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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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Graph DBMS
RDF store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

greenplum.org

ignitetech.com/softwarelibrary/infobrightdb

www.stardog.com

www.warp10.io

Technical documentation

docs.greenplum.org

docs.stardog.com

www.warp10.io/content/02_Getting_started

Developer

Pivotal Software Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Stardog-Union

SenX

Initial release

2005

2010

2015

Current release

7.0.0, September 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache License 2.0

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

Java

Server operating systems

Linux

Linux
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

HTTP API
Jupyter
WebSocket

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

yes

WarpScript

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication in HA-Cluster

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

relationships in graphs

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

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users and roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

Recent citations in the news

Chapter 1. Introducing the Greenplum Database
6 December 2018, O'Reilly Media

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale
9 September 2019, AWS Blog

Greenplum 6 ventures outside the analytic box
19 March 2019, ZDNet

EMC and Greenplum Dress Elephant for IT Parade
8 December 2011, WIRED

EMC Introduces Breakthrough 'Big Data' Computing System
13 October 2010, PR Newswire

provided by Google News

Launched Just A Year Ago, Open-Source Scality S3 Server Gains Extraordinary Momentum As It Simplifies The Life Of Developers
28 June 2017, PR Newswire

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