DBMS > CouchDB vs. Greenplum vs. jBASE vs. MySQL vs. Splice Machine

System Properties Comparison CouchDB vs. Greenplum vs. jBASE vs. MySQL vs. Splice Machine

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.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

A robust multi-value DBMS comprising development tools and middleware

Widely used open source RDBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Key/Value like access via memcached API

Relational DBMS

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	9.30
Rank	#45	Overall
	#7	Document stores

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

couchdb.apache.org

greenplum.org

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

www.mysql.com

splicemachine.com

Technical documentation

docs.couchdb.org/en/stable

docs.greenplum.org

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

dev.mysql.com/doc

splicemachine.com/how-it-works

Developer

Apache Software Foundation

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

Pivotal Software Inc.

Rocket Software (formerly Zumasys)

Oracle

since 2010, originally MySQL AB, then Sun

Splice Machine

Initial release

2005

1991

1995

2014

Current release

3.3.3, December 2023

7.0.0, September 2023

5.7

8.3.0, January 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

C and C++

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux

AIX
Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

since Version 4.2

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

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

C
Java
Perl
Python
R

.Net
Basic
Jabbascript
Java

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

yes

proprietary syntax

yes

Java

Triggers

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

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

Access rights for users, groups and roles according to SQL-standard

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