DBMS > Couchbase vs. Geode vs. mSQL vs. RDF4J

System Properties Comparison Couchbase vs. Geode vs. mSQL vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

mSQL (Mini SQL) is a simple and lightweight RDBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	1.51
Rank	#147	Overall
	#25	Key-value stores

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

www.couchbase.com

geode.apache.org

hughestech.com.au/products/msql

rdf4j.org

Technical documentation

docs.couchbase.com

geode.apache.org/docs

rdf4j.org/documentation

Developer

Couchbase, Inc.

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Hughes Technologies

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2011

2002

1994

2004

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1.1, February 2017

4.4, October 2021

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

free licenses can be provided

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Go and Erlang

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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.

Secondary indexes

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language (OQL)

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
All JVM based languages
C++
Groovy
Java
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions

yes

Triggers

yes

via the TAP protocol

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

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

selectable on a per-operation basis

Eventual Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes, on a single node

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights per client and object definable

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