DBMS > Amazon Redshift vs. Ehcache vs. Transwarp ArgoDB

System Properties Comparison Amazon Redshift vs. Ehcache vs. Transwarp ArgoDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A widely adopted Java cache with tiered storage options

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Search engine

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

aws.amazon.com/redshift

www.ehcache.org

www.transwarp.cn/en/product/argodb

Technical documentation

docs.aws.amazon.com/redshift

www.ehcache.org/documentation

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Amazon (based on PostgreSQL)

Terracotta Inc, owned by Software AG

Transwarp

Initial release

2012

2009

Current release

3.10.0, March 2022

License

Commercial or Open Source

commercial

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

Server operating systems

hosted

All OS with a Java VM

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

Supported programming languages

All languages supporting JDBC/ODBC

Java

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.