DBMS > Amazon Redshift vs. BigObject vs. eXtremeDB vs. Greenplum

System Properties Comparison Amazon Redshift vs. BigObject vs. eXtremeDB vs. Greenplum

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

Natively in-memory DBMS with options for persistency, high-availability and clustering

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.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Website

aws.amazon.com/redshift

bigobject.io

www.mcobject.com

greenplum.org

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

www.mcobject.com/docs/extremedb.htm

docs.greenplum.org

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

McObject

Pivotal Software Inc.

Initial release

2012

2015

2001

2005

Current release

8.2, 2021

7.0.0, September 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Apache 2.0

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 and C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

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.

support of XML interfaces available

yes

since Version 4.2

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

with the option: eXtremeSQL

yes

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
Java
Lua
Python
Scala

C
Java
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

yes

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning / sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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