DBMS > Amazon Redshift vs. Couchbase vs. CouchDB vs. Ehcache vs. Microsoft Access

System Properties Comparison Amazon Redshift vs. Couchbase vs. CouchDB vs. Ehcache vs. Microsoft Access

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A widely adopted Java cache with tiered storage options

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

using the Geocouch extension

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

aws.amazon.com/redshift

www.couchbase.com

couchdb.apache.org

www.ehcache.org

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

docs.aws.amazon.com/redshift

docs.couchbase.com

docs.couchdb.org/en/stable

www.ehcache.org/documentation

developer.microsoft.com/en-us/access

Developer

Amazon (based on PostgreSQL)

Couchbase, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Terracotta Inc, owned by Software AG

Microsoft

Initial release

2012

2011

2005

2009

1992

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.3.3, December 2023

3.10.0, March 2022

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

commercial

Bundled with Microsoft Office

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

C, C++, Go and Erlang

Erlang

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

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

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

but not compliant to any SQL standard

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP/JSON API

JCache

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Java

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

in Python

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

View functions in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

via the TAP protocol

yes

Cache Event Listeners

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

Sharding

improved architecture with release 2.0

Sharding

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

yes

by using Terracotta Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual 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

atomic operations within a single document possible

yes

supports JTA and can work as an XA resource

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

but no files for transaction logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users can be defined per database

a simple user-level security was built in till version Access 2003

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