DBMS > Cassandra vs. Newts vs. RDF4J vs. Sphinx vs. Yaacomo

System Properties Comparison Cassandra vs. Newts vs. RDF4J vs. Sphinx vs. Yaacomo

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB info

Optimized for write access

Time Series DBMS based on Cassandra

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

Open source search engine for searching in data from different sources, e.g. relational databases

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	120.36
Rank	#11	Overall
	#1	Wide column stores

Score	0.02
Rank	#323	Overall
	#29	Time Series DBMS

Score	0.39
Rank	#223	Overall
	#11	RDF stores

Score	7.26
Rank	#48	Overall
	#5	Search engines

Score	0.00
Rank	#334	Overall
	#136	Relational DBMS

Website

cassandra.apache.org

opennms.github.io/newts

rdf4j.org

sphinxsearch.com

yaacomo.com

Technical documentation

cassandra.apache.org/doc/latest

github.com/OpenNMS/newts/wiki

docs.rdf4j.org

sphinxsearch.com/docs

Developer

Apache Software Foundation info

Apache top level project, originally developped by Facebook

OpenNMS Group

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

Sphinx Technologies Inc.

Q2WEB GmbH

Initial release

2008

2014

2004

2001

2009

Current release

3.11.6, February 2020

3.1.1, October 2018

License

Commercial or Open Source

Open Source info

Apache version 2

Open Source info

Apache 2.0

Open Source info

Eclipse Distribution License (EDL), v1.0.

Open Source info

GPL version 2, commercial licence available

commercial

Cloud-based only info

Only available as a cloud service

DBaaS offerings (sponsored links) info

Database as a Service

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

Implementation language

Java

C++

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Android
Linux
Windows

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

XML support info

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

restricted info

only equality queries, not always the best performing solution

yes

full-text index on all search fields

yes

SQL

Support of SQL

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

SQL-like query language (SphinxQL)

yes

APIs and other access methods

Proprietary protocol info

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

HTTP REST
Java API

Java API
RIO info

RDF Input/Output
Sail API
SeRQL info

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Proprietary protocol

JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript info

Node.js
Perl
PHP
Python
Ruby
Scala

Java

Java
PHP
Python

C++

unofficial client library
Java
Perl info

unofficial client library
PHP
Python
Ruby info

unofficial client library

Server-side scripts info

Stored procedures

yes

Triggers

yes

Partitioning methods info

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

based on Cassandra

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

Replication methods info

Methods for redundantly storing data on multiple nodes

selectable replication factor info

Representation of geographical distribution of servers is possible

selectable replication factor info

based on Cassandra

none

Master-slave replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts info

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency info

can be individually decided for each write operation

Eventual Consistency info

based on Cassandra
Immediate Consistency info

based on Cassandra

Immediate Consistency

Foreign keys info

Referential integrity

yes

Transaction concepts info

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

Atomicity and isolation are supported for single operations

ACID

Isolation support depends on the API used

ACID

Concurrency info

Support for concurrent manipulation of data

yes

Durability info

Support for making data persistent

yes

in-memory storage is supported as well

yes

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities info

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

yes

User concepts info

Access control

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

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...
» more

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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