DBMS > Amazon Redshift vs. Oracle Coherence vs. Valentina Server

System Properties Comparison Amazon Redshift vs. Oracle Coherence vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Oracles in-memory data grid solution

Object-relational database and reports server

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	21.04
Rank	#34	Overall
	#21	Relational DBMS

Score	2.69
Rank	#124	Overall
	#23	Key-value stores

Score	0.33
Rank	#317	Overall
	#140	Relational DBMS

Website

aws.amazon.com/redshift

www.oracle.com/java/coherence

www.valentina-db.net

Technical documentation

docs.aws.amazon.com/redshift

docs.oracle.com/en/middleware/standalone/coherence

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Amazon (based on PostgreSQL)

Oracle

Paradigma Software

Initial release

2012

2007

1999

Current release

12c, September 2016

5.7.5

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JCache
JPA
RESTful HTTP API

ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C++
Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

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