DBMS > Faircom EDGE vs. Microsoft SQL Server vs. RDF4J vs. Splunk

System Properties Comparison Faircom EDGE vs. Microsoft SQL Server vs. RDF4J vs. Splunk

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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

Microsofts flagship relational DBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Analytics Platform for Big Data

Primary database model

Key-value store
Relational DBMS

Relational DBMS

RDF store

Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

www.faircom.com/products/faircom-edge

www.microsoft.com/en-us/sql-server

rdf4j.org

www.splunk.com

Technical documentation

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

learn.microsoft.com/en-US/sql/sql-server

rdf4j.org/documentation

docs.splunk.com/Documentation/Splunk

Developer

FairCom Corporation

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Splunk Inc.

Initial release

1979

1989

2004

2003

Current release

V3, October 2020

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

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

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

Splunk Search Processing Language for search commands

APIs and other access methods

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

Supported programming languages

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java
PHP
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes, but depending on the SQL-Server Edition

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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.

fine grained access rights according to SQL-standard

Access rights for users and roles

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