DBMS > Ehcache vs. Faircom EDGE vs. Microsoft SQL Server vs. Stardog

System Properties Comparison Ehcache vs. Faircom EDGE vs. Microsoft SQL Server vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

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

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

Primary database model

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	0.03
Rank	#380	Overall
	#59	Key-value stores
	#157	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.ehcache.org

www.faircom.com/products/faircom-edge

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

www.stardog.com

Technical documentation

www.ehcache.org/documentation

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

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

docs.stardog.com

Developer

Terracotta Inc, owned by Software AG

FairCom Corporation

Microsoft

Stardog-Union

Initial release

2009

1979

1989

2010

Current release

3.10.0, March 2022

V3, October 2020

SQL Server 2022, November 2022

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Restricted, free version available

commercial

restricted free version is available

commercial

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

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

ANSI C, C++

C++

Java

Server operating systems

All OS with a Java VM

Android
Linux

ARM, x86
Raspbian
Windows

Linux
Windows

Linux
macOS
Windows

Data scheme

schema-free

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

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

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

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

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

APIs and other access methods

JCache

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)

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

Supported programming languages

Java

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

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

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

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Cache Event Listeners

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

File partitioning

Customizable business rules for partitioning

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes, but depending on the SQL-Server Edition

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency
Tunable Consistency

Immediate Consistency

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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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