DBMS > BaseX vs. Cassandra vs. InfinityDB vs. Newts vs. RDF4J

System Properties Comparison BaseX vs. Cassandra vs. InfinityDB vs. Newts vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

Time Series DBMS based on Cassandra

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

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	1.90
Rank	#136	Overall
	#4	Native XML DBMS

Score	103.86
Rank	#12	Overall
	#1	Wide column stores

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

basex.org

cassandra.apache.org

boilerbay.com

opennms.github.io/newts

rdf4j.org

Technical documentation

docs.basex.org

cassandra.apache.org/doc/latest

boilerbay.com/infinitydb/manual

github.com/OpenNMS/newts/wiki

rdf4j.org/documentation

Developer

BaseX GmbH

Apache Software Foundation

Apache top level project, originally developped by Facebook

Boiler Bay Inc.

OpenNMS Group

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

Initial release

2007

2008

2002

2014

2004

Current release

10.7, August 2023

4.1.3, July 2023

4.0

License

Commercial or Open Source

Open Source

BSD license

Open Source

Apache version 2

commercial

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

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

XQuery supports types

yes

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

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

restricted

only equality queries, not always the best performing solution

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

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

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

HTTP REST
Java API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Java

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

none

selectable replication factor

based on Cassandra

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

can be individually decided for each write operation

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

multiple readers, single writer

Atomicity and isolation are supported for single operations

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

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.

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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