DBMS > InfinityDB vs. PouchDB vs. Quasardb vs. RDF4J

System Properties Comparison InfinityDB vs. PouchDB vs. Quasardb vs. RDF4J

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A Java embedded Key-Value Store which extends the Java Map interface

JavaScript DBMS with an API inspired by CouchDB

Distributed, high-performance timeseries database

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	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

Technical documentation

boilerbay.com/infinitydb/manual

pouchdb.com/guides

doc.quasar.ai/master

rdf4j.org/documentation

Developer

Boiler Bay Inc.

Apache Software Foundation

quasardb

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

Initial release

2002

2012

2009

2004

Current release

4.0

7.1.1, June 2019

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Java

JavaScript

C++

Java

Server operating systems

All OS with a Java VM

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

BSD
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

integer and binary

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

manual creation possible, using inversions based on multi-value capability

yes

via views

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

JavaScript

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

by using LevelDB

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

Transient mode

User concepts

Access control

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

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

show all

Recent citations in the news

Getting Started with PouchDB Client-Side JavaScript Database
7 September 2016, SitePoint

Create Offline Web Apps Using Service Workers & PouchDB
7 March 2017, SitePoint

Building an Offline First App with PouchDB
10 March 2014, SitePoint

provided by Google News

NVIDIA to Present Innovations at Hot Chips That Boost Data Center Performance and Energy Efficiency
23 August 2024, NVIDIA Blog

Exploring secular variation of the gravitational constant from high-resolution quasar spectra
6 July 2024, Nature.com

Record quasar is most luminous object in the universe
20 February 2024, EarthSky

When a Quasar Remote Access Tool Falls Into the Wrong Hands
23 February 2024, Darktrace

Data Release 1: The UVES Spectral Quasar Absorption Database (SQUAD)
8 March 2019, ESO.org

provided by Google News

Share this page