DBMS > Lovefield vs. Memcached vs. Prometheus vs. RDF4J

System Properties Comparison Lovefield vs. Memcached vs. Prometheus vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

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

Open-source Time Series DBMS and monitoring system

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

Primary database model

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

google.github.io/lovefield

www.memcached.org

prometheus.io

rdf4j.org

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

github.com/memcached/memcached/wiki

prometheus.io/docs

rdf4j.org/documentation

Developer

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

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

Initial release

2014

2003

2015

2004

Current release

2.1.12, February 2017

1.6.25, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD license

Open Source

Apache 2.0

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Unix
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Proprietary protocol

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

JavaScript

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Foreign keys

Referential integrity

yes

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 or the cloud service Firebase Realtime Database

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

using MemoryDB

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

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