DBMS > Greenplum vs. Hawkular Metrics vs. Sadas Engine vs. Ultipa

System Properties Comparison Greenplum vs. Hawkular Metrics vs. Sadas Engine vs. Ultipa

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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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

Technical documentation

docs.greenplum.org

www.hawkular.org/hawkular-metrics/docs/user-guide

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.ultipa.com/document

Developer

Pivotal Software Inc.

Community supported by Red Hat

SADAS s.r.l.

Ultipa

Initial release

2005

2014

2006

2019

Current release

7.0.0, September 2023

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

free trial version available

commercial

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

C++

Server operating systems

Linux

Linux
OS X
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

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.

yes

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

HTTP REST

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

Go
Java
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

none

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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More resources

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