DBMS > CouchDB vs. Datastax Enterprise vs. MySQL

System Properties Comparison CouchDB vs. Datastax Enterprise vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

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

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Widely used open source RDBMS

Primary database model

Document store

Wide column store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Document store
Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

couchdb.apache.org

www.datastax.com/products/datastax-enterprise

www.mysql.com

Technical documentation

docs.couchdb.org/en/stable

docs.datastax.com

dev.mysql.com/doc

Developer

Apache Software Foundation

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

DataStax

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2005

2011

1995

Current release

3.3.3, December 2023

6.8, April 2020

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Erlang

Java

C and C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

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

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

no "single point of failure"

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware, advanced replication for edge computing

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

atomic operations within a single document possible

Atomicity and isolation are supported for single operations

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

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

Access rights for users can be defined per database

Access rights for users can be defined per object

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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