DBMS > CouchDB vs. Kinetica vs. MySQL vs. SAP HANA vs. WakandaDB

System Properties Comparison CouchDB vs. Kinetica vs. MySQL vs. SAP HANA vs. WakandaDB

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.

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

In-memory, column based data store. Available as appliance or cloud service

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Object oriented DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	10.26
Rank	#45	Overall
	#7	Document stores

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Website

couchdb.apache.org

www.kinetica.com

www.mysql.com

www.sap.com/products/hana.html

wakanda.github.io

Technical documentation

docs.couchdb.org/en/stable

docs.kinetica.com

dev.mysql.com/doc

help.sap.com/hana

wakanda.github.io/doc

Developer

Apache Software Foundation

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

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

SAP

Wakanda SAS

Initial release

2005

2012

1995

2010

2012

Current release

3.3.3, December 2023

7.1, August 2021

8.3.0, January 2024

2.0 SPS07 (April 4, 2023), April 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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Implementation language

Erlang

C, C++

C and C++

C++, JavaScript

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Linux
OS X
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

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

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

JavaScript

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

yes

proprietary syntax

SQLScript, R

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

yes

none

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

yes

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users can be defined per database

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

yes

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