DBMS > EXASOL vs. Fauna vs. RDFox vs. SAP HANA

System Properties Comparison EXASOL vs. Fauna vs. RDFox vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

High performance knowledge graph and semantic reasoning engine

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.exasol.com

fauna.com

www.oxfordsemantic.tech

www.sap.com/products/hana.html

Technical documentation

www.exasol.com/resources

docs.fauna.com

docs.oxfordsemantic.tech

help.sap.com/hana

Developer

Exasol

Fauna, Inc.

Oxford Semantic Technologies

SAP

Initial release

2000

2014

2017

2010

Current release

6.0, Septermber 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Scala

C++

Server operating systems

hosted

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

yes

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

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
Java

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Access rights for users, groups and roles according to SQL-standard

Identity management, authentication, and access control

Roles, resources, and access types

yes

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