DBMS > Memcached vs. PouchDB vs. RDF4J

System Properties Comparison Memcached vs. PouchDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

In-memory key-value store, originally intended for caching

JavaScript DBMS with an API inspired by CouchDB

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

Primary database model

Key-value store

Document store

RDF store

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

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

www.memcached.org

pouchdb.com

rdf4j.org

Technical documentation

github.com/memcached/memcached/wiki

pouchdb.com/guides

rdf4j.org/documentation

Developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Apache Software Foundation

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

Initial release

2003

2012

2004

Current release

1.6.25, March 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

BSD license

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

JavaScript

Java

Server operating systems

FreeBSD
Linux
OS X
Unix
Windows

server-less, requires a JavaScript environment (browser, Node.js)

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

via views

yes

SQL

Support of SQL

APIs and other access methods

Proprietary protocol

HTTP REST

only for PouchDB Server
JavaScript API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

JavaScript

Java
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

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More resources

DB-Engines blog posts

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3 October 2012, Matthias Gelbmann, Paul Andlinger

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New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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