DBMS > RDFox vs. RethinkDB vs. Spark SQL

System Properties Comparison RDFox vs. RethinkDB vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

High performance knowledge graph and semantic reasoning engine

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Graph DBMS
RDF store

Document store

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	0.24
Rank	#309	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	2.84
Rank	#106	Overall
	#19	Document stores

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

www.oxfordsemantic.tech

rethinkdb.com

spark.apache.org/sql

Technical documentation

docs.oxfordsemantic.tech

rethinkdb.com/docs

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Oxford Semantic Technologies

The Linux Foundation

since July 2017

Apache Software Foundation

Initial release

2017

2009

2014

Current release

6.0, Septermber 2022

2.4.1, August 2020

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

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

C++

Scala

Server operating systems

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

RDF schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC

Supported programming languages

C
Java

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Java
Python
R
Scala

Server-side scripts

Stored procedures

Triggers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

replication via a shared file system

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

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

yes

users and table-level permissions

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

Meet some database management systems you are likely to hear more about in the future
4 August 2014, Paul Andlinger

show all

Recent citations in the news

Use semantic reasoning to infer new facts from your RDF graph by integrating RDFox with Amazon Neptune | Amazon ...
20 February 2023, AWS Blog

Eight interesting open-source graph databases
3 January 2023, INDIAai

Financial Crime Discovery using Amazon EKS and Graph Databases | Amazon Web Services
1 February 2022, AWS Blog

provided by Google News

An introduction to building realtime apps with RethinkDB
9 July 2022, devm.io

Stripe acquires team behind NoSQL database startup RethinkDB
5 October 2016, VentureBeat

Realtime App Development with RethinkDB and React Native — SitePoint
17 June 2016, SitePoint

MongoDB: The Popular Database for IoT
15 August 2023, Open Source For You

RethinkDB is dead, and MongoDB isn't what killed it
24 January 2017, TechRepublic

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News

Share this page