DBMS > Amazon Redshift vs. Coveo vs. Ehcache

System Properties Comparison Amazon Redshift vs. Coveo vs. Ehcache

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

A widely adopted Java cache with tiered storage options

Primary database model

Relational DBMS

Search engine

Key-value store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.11
Rank	#118	Overall
	#11	Search engines

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

Website

aws.amazon.com/redshift

www.coveo.com

www.ehcache.org

Technical documentation

docs.aws.amazon.com/redshift

docs.coveo.com

www.ehcache.org/documentation

Developer

Amazon (based on PostgreSQL)

Coveo

Terracotta Inc, owned by Software AG

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

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

Data scheme

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

schema-free

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

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JCache

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

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

yes

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

yes

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

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

granular access controls, API key management, content filters

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