DBMS > Cachelot.io vs. Oracle Rdb vs. RDFox vs. Sphinx

System Properties Comparison Cachelot.io vs. Oracle Rdb vs. RDFox vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

High performance knowledge graph and semantic reasoning engine

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

cachelot.io

www.oracle.com/database/technologies/related/rdb.html

www.oxfordsemantic.tech

sphinxsearch.com

Technical documentation

www.oracle.com/database/technologies/related/rdb-doc.html

docs.oxfordsemantic.tech

sphinxsearch.com/docs

Developer

Oracle, originally developed by Digital Equipment Corporation (DEC)

Oxford Semantic Technologies

Sphinx Technologies Inc.

Initial release

2015

1984

2017

2001

Current release

7.4.1.1, 2021

6.0, Septermber 2022

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

GPL version 2, commercial licence available

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

C++

Server operating systems

FreeBSD
Linux
OS X

HP Open VMS

Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

RDF schemas

yes

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

Memcached protocol

RESTful HTTP API
SPARQL 1.1

Proprietary protocol

Supported programming languages

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

C
Java

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

replication via a shared file system

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Roles, resources, and access types

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More resources

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