DBMS > Amazon Redshift vs. Greenplum vs. Hazelcast vs. IRONdb vs. UniData,UniVerse

System Properties Comparison Amazon Redshift vs. Greenplum vs. Hazelcast vs. IRONdb vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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 widely adopted in-memory data grid

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store

JSON support with IMDG 3.12

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

aws.amazon.com/redshift

greenplum.org

hazelcast.com

www.circonus.com/solutions/time-series-database/

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.aws.amazon.com/redshift

docs.greenplum.org

hazelcast.org/imdg/docs

docs.circonus.com/irondb/category/getting-started

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Amazon (based on PostgreSQL)

Pivotal Software Inc.

Hazelcast

Circonus LLC.

Rocket Software

Initial release

2012

2005

2008

2017

1985

Current release

7.0.0, September 2023

5.3.6, November 2023

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

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

Java

C and C++

Server operating systems

hosted

Linux

All OS with a Java VM

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

optional

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

the object must implement a serialization strategy

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

HTTP API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

All languages supporting JDBC/ODBC

C
Java
Perl
Python
R

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Event Listeners, Executor Services

yes, in Lua

yes

Triggers

yes

Events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Replicated Map

configurable replication factor, datacenter aware

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

configurable

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

Role-based access control

Access rights according to SQL-standard and operating system based

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