DBMS > Faircom EDGE vs. Hazelcast vs. Snowflake vs. Stardog vs. SWC-DB

System Properties Comparison Faircom EDGE vs. Hazelcast vs. Snowflake vs. Stardog vs. SWC-DB

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

A widely adopted in-memory data grid

Cloud-based data warehousing service for structured and semi-structured data

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

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store
Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series 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	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.faircom.com/products/faircom-edge

hazelcast.com

www.snowflake.com

www.stardog.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

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

hazelcast.org/imdg/docs

docs.snowflake.net/manuals/index.html

docs.stardog.com

Developer

FairCom Corporation

Hazelcast

Snowflake Computing Inc.

Stardog-Union

Alex Kashirin

Initial release

1979

2008

2014

2010

2020

Current release

V3, October 2020

5.3.6, November 2023

7.3.0, May 2020

0.5, April 2021

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2; commercial licenses available

commercial

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

Open Source

GPL V3

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

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

hosted

Linux
macOS
Windows

Linux

Data scheme

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

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free and OWL/RDFS-schema support

schema-free

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

the object must implement a serialization strategy

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

SQL-like query language

yes

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

SQL-like query language

APIs and other access methods

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

JCache
JPA
Memcached protocol
RESTful HTTP API

CLI Client
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

Proprietary protocol
Thrift

Supported programming languages

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Event Listeners, Executor Services

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Events

similar concept for controling cloud resources

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Replicated Map

yes

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
Tunable Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

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

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

User concepts

Access control

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

Role-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles

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