DBMS > Amazon Redshift vs. Ehcache vs. H2 vs. IBM Cloudant vs. OceanBase

System Properties Comparison Amazon Redshift vs. Ehcache vs. H2 vs. IBM Cloudant vs. OceanBase

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Database as a Service offering based on Apache CouchDB

A distributed, high available RDBMS compatible with Oracle and MySQL

Primary database model

Secondary database models

Spatial DBMS

Document store
Wide column store

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Trend Chart

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	1.57
Rank	#149	Overall
	#69	Relational DBMS

Website

aws.amazon.com/redshift

www.ehcache.org

www.h2database.com

www.ibm.com/products/cloudant

en.oceanbase.com

Technical documentation

docs.aws.amazon.com/redshift

www.ehcache.org/documentation

www.h2database.com/html/main.html

cloud.ibm.com/docs/Cloudant

en.oceanbase.com/docs/oceanbase-database

Developer

Amazon (based on PostgreSQL)

Terracotta Inc, owned by Software AG

Thomas Mueller

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

OceanBase

previously Alibaba and Ant Group

Initial release

2012

2009

2005

2010

Current release

3.10.0, March 2022

2.2.220, July 2023

4.3.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

Commercial license 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

Erlang

C++

Server operating systems

hosted

All OS with a Java VM

hosted

Linux

Data scheme

yes

schema-free

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

APIs and other access methods

JDBC
ODBC

JCache

JDBC
ODBC

RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Supported programming languages

All languages supporting JDBC/ODBC

Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures and User-Defined Functions

View functions (Map-Reduce) in JavaScript

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

Sharding

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

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

yes

supports JTA and can work as an XA resource

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Optimistic locking

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

Access rights for users can be defined per database

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

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