DBMS > Amazon Redshift vs. EXASOL vs. Hawkular Metrics vs. OpenEdge

System Properties Comparison Amazon Redshift vs. EXASOL vs. Hawkular Metrics vs. OpenEdge

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Application development environment with integrated database management system

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Website

aws.amazon.com/redshift

www.exasol.com

www.hawkular.org

www.progress.com/openedge

Technical documentation

docs.aws.amazon.com/redshift

www.exasol.com/resources

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

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Amazon (based on PostgreSQL)

Exasol

Community supported by Red Hat

Progress Software Corporation

Initial release

2012

2000

2014

1984

Current release

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Server operating systems

hosted

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

close to SQL 92

APIs and other access methods

JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

HTTP REST

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Java
Lua
Python
R

Go
Java
Python
Ruby

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

informational only, not enforced by the system

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

Users and groups

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