DBMS > Amazon Redshift vs. EsgynDB vs. Faircom EDGE vs. GraphDB vs. H2GIS

System Properties Comparison Amazon Redshift vs. EsgynDB vs. Faircom EDGE vs. GraphDB vs. H2GIS

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Spatial extension of H2

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Graph DBMS
RDF store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

aws.amazon.com/redshift

www.esgyn.cn

www.faircom.com/products/faircom-edge

www.ontotext.com

www.h2gis.org

Technical documentation

docs.aws.amazon.com/redshift

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

graphdb.ontotext.com/documentation

www.h2gis.org/docs/home

Social network pages

Developer

Amazon (based on PostgreSQL)

Esgyn

FairCom Corporation

Ontotext

CNRS

Initial release

2012

2015

1979

2000

2013

Current release

V3, October 2020

10.4, October 2023

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

LGPL 3.0

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

C++, Java

ANSI C, C++

Java

Server operating systems

hosted

Linux

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM
Linux
OS X
Windows

Data scheme

yes

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

schema-free and OWL/RDFS-schema support; RDF shapes

yes

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

Secondary indexes

restricted

yes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

ANSI SQL queries

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

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

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

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

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

.Net, JavaScript, C/C++

well-defined plugin interfaces; JavaScript server-side extensibility

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

yes

based on H2

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, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

when using SQL

yes

Constraint checking

yes

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

yes, multi-version concurrency control (MVCC)

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 access rights according to SQL-standard

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

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

yes

based on H2

More information provided by the system vendor

Specific characteristics

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Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
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Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
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Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
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Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
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Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
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