DBMS > Amazon Neptune vs. Faircom DB vs. OpenQM vs. Stardog

System Properties Comparison Amazon Neptune vs. Faircom DB vs. OpenQM vs. Stardog

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Primary database model

Graph DBMS
RDF store

Key-value store
Relational DBMS

Multivalue DBMS

Graph DBMS
RDF store

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

Score	2.58
Rank	#112	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

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

Website

aws.amazon.com/neptune

www.faircom.com/products/faircom-db

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.stardog.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.stardog.com

Developer

Amazon

FairCom Corporation

Rocket Software, originally Martin Phillips

Stardog-Union

Initial release

2017

1979

1993

2010

Current release

V12, November 2020

3.4-12

7.3.0, May 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

GPLv2, extended commercial license 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

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

Java

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

yes

with some exceptions

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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 with proprietary extensions

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

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

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

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

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

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

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

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationships in graphs

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

Yes, tunable from durable to delayed durability to in-memory

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Fine grained access rights according to SQL-standard with additional protections for files

Access rights can be defined down to the item level

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Uncover hidden connections in unstructured financial data with Amazon Bedrock and Amazon Neptune | Amazon Web ...
17 April 2024, AWS Blog

Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ...
29 November 2023, AWS Blog

Create a Virtual Knowledge Graph with Amazon Neptune and an Amazon S3 data lake | Amazon Web Services
21 February 2024, AWS Blog

Visualize and explore knowledge graphs quickly by connecting metaphactory to Amazon Neptune | Amazon Web ...
22 January 2024, AWS Blog

Improve availability of Amazon Neptune during engine upgrade using blue/green deployment | Amazon Web Services
11 September 2023, AWS Blog

provided by Google News

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

World's First Converged IIoT Hub to be Showcased at IoT Tech Expo
3 September 2021, Automation.com

provided by Google News

Share this page