DBMS > Faircom EDGE vs. Fauna vs. RDFox vs. Stardog vs. STSdb

System Properties Comparison Faircom EDGE vs. Fauna vs. RDFox vs. Stardog vs. STSdb

Editorial information provided by DB-Engines

Name

Description

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store
Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Graph DBMS
RDF store

Key-value store

Secondary database models

Relational DBMS

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

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	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	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.faircom.com/products/faircom-edge

fauna.com

www.oxfordsemantic.tech

www.stardog.com

github.com/STSSoft/STSdb4

Technical documentation

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

docs.fauna.com

docs.oxfordsemantic.tech

docs.stardog.com

Developer

FairCom Corporation

Fauna, Inc.

Oxford Semantic Technologies

Stardog-Union

STS Soft SC

Initial release

1979

2014

2017

2010

2011

Current release

V3, October 2020

6.0, Septermber 2022

7.3.0, May 2020

4.0.8, September 2015

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

Scala

C++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Linux
macOS
Windows

Windows

Data scheme

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

schema-free

yes

RDF schemas

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

primitive types and user defined types (classes)

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.

yes

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

ANSI SQL queries

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

.NET Client API

Supported programming languages

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
Java

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

horizontal partitioning

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

replication via a shared file system

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

when using SQL

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Identity management, authentication, and access control

Roles, resources, and access types

Access rights for users and roles

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