DBMS > CouchDB vs. Hazelcast vs. Kinetica vs. MySQL vs. UniData,UniVerse

System Properties Comparison CouchDB vs. Hazelcast vs. Kinetica vs. MySQL vs. UniData,UniVerse

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.

A widely adopted in-memory data grid

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Document store

Key-value store

Relational DBMS

Key/Value like access via memcached API

Multivalue DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store

JSON support with IMDG 3.12

Spatial DBMS
Time Series 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	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.couchdb.org/en/stable

hazelcast.org/imdg/docs

docs.kinetica.com

dev.mysql.com/doc

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Apache Software Foundation

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

Hazelcast

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

Rocket Software

Initial release

2005

2008

2012

1995

1985

Current release

3.3.3, December 2023

5.3.6, November 2023

7.1, August 2021

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

Java

C, C++

C and C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Event Listeners, Executor Services

user defined functions

yes

proprietary syntax

yes

Triggers

yes

Events

yes

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

yes

U2 Basic

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Replicated Map

Source-replica replication

Multi-source replication
Source-replica 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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency or Eventual Consistency depending on configuration

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

one or two-phase-commit; repeatable reads; read commited

ACID

not for MyISAM storage engine

ACID

configurable

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

Role-based access control

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

Access rights according to SQL-standard and operating system based

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