DBMS > Oracle NoSQL vs. RDFox vs. Riak KV vs. Sphinx

System Properties Comparison Oracle NoSQL vs. RDFox vs. Riak KV vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

High performance knowledge graph and semantic reasoning engine

Distributed, fault tolerant key-value store

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

Primary database model

Document store
Key-value store
Relational DBMS

Graph DBMS
RDF store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Search engine

Secondary database models

Relational DBMS

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

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

www.oracle.com/database/nosql/technologies/nosql

www.oxfordsemantic.tech

sphinxsearch.com

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.oxfordsemantic.tech

www.tiot.jp/riak-docs/riak/kv/latest

sphinxsearch.com/docs

Developer

Oracle

Oxford Semantic Technologies

OpenSource, formerly Basho Technologies

Sphinx Technologies Inc.

Initial release

2011

2017

2009

2001

Current release

24.1, May 2024

6.0, Septermber 2022

3.2.0, December 2022

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Open Source

Apache version 2, commercial enterprise edition

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

Java

C++

Erlang

C++

Server operating systems

Linux
Solaris SPARC/x86

Linux
macOS
Windows

Linux
OS X

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

RDF schemas

schema-free

yes

Typing

predefined data types such as float or date

optional

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

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

HTTP API
Native Erlang Interface

Proprietary protocol

Supported programming languages

C
C#
Go
Java
JavaScript (Node.js)
Python

C
Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

replication via a shared file system

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

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

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

User concepts

Access control

Access rights for users and roles

Roles, resources, and access types

yes, using Riak Security

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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