DBMS > CockroachDB vs. CouchDB vs. LeanXcale vs. MySQL

System Properties Comparison CockroachDB vs. CouchDB vs. LeanXcale vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Widely used open source RDBMS

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

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

Score	6.10
Rank	#58	Overall
	#33	Relational DBMS

Score	10.26
Rank	#45	Overall
	#7	Document stores

Score	0.35
Rank	#283	Overall
	#41	Key-value stores
	#128	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Website

www.cockroachlabs.com

couchdb.apache.org

www.leanxcale.com

www.mysql.com

Technical documentation

www.cockroachlabs.com/docs

docs.couchdb.org/en/stable

dev.mysql.com/doc

Developer

Cockroach Labs

Apache Software Foundation

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

LeanXcale

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2015

2005

2015

1995

Current release

23.1.1, May 2023

3.3.3, December 2023

8.3.0, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

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

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Implementation language

Erlang

C and C++

Server operating systems

Linux
macOS
Windows

Android
BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

dynamic schema

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

yes, wire compatible with PostgreSQL

yes

through Apache Derby

yes

with proprietary extensions

APIs and other access methods

JDBC

RESTful HTTP/JSON API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

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

C
Java
Scala

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

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

improved architecture with release 2.0

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

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

Immediate Consistency

Eventual Consistency

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

ACID

atomic operations within a single document possible

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

Role-based access control

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

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