DBMS > EsgynDB vs. Faircom EDGE vs. NuoDB vs. Stardog

System Properties Comparison EsgynDB vs. Faircom EDGE vs. NuoDB vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS
RDF store

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

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

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

Score	0.99
Rank	#195	Overall
	#92	Relational DBMS

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

Website

www.esgyn.cn

www.faircom.com/products/faircom-edge

www.3ds.com/nuodb-distributed-sql-database

www.stardog.com

Technical documentation

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

doc.nuodb.com

docs.stardog.com

Developer

Esgyn

FairCom Corporation

Dassault Systèmes

originally NuoDB, Inc.

Stardog-Union

Initial release

2015

1979

2013

2010

Current release

V3, October 2020

7.3.0, May 2020

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

limited edition free

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

C++, Java

ANSI C, C++

C++

Java

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

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

ADO.NET
JDBC
ODBC

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

ADO.NET
JDBC
ODBC

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

All languages supporting JDBC/ODBC/ADO.Net

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

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

Java, SQL

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

Sharding

File partitioning

Customizable business rules for partitioning

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Managed transparently by NuoDB

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

MVCC

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

Temporary table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Standard SQL roles/ privileges, Administrative Users

Access rights for users and roles

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