DBMS > Faircom EDGE vs. Quasardb vs. RavenDB vs. Snowflake vs. TerminusDB

System Properties Comparison Faircom EDGE vs. Quasardb vs. RavenDB vs. Snowflake vs. TerminusDB

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

Distributed, high-performance timeseries database

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key-value store
Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
RDF store

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	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

www.faircom.com/products/faircom-edge

Technical documentation

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

doc.quasar.ai/master

ravendb.net/docs

docs.snowflake.net/manuals/index.html

terminusdb.github.io/terminusdb/#

Developer

FairCom Corporation

quasardb

Hibernating Rhinos

Snowflake Computing Inc.

DataChemist Ltd.

Initial release

1979

2009

2010

2014

2018

Current release

V3, October 2020

3.14.1, January 2024

5.4, July 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

AGPL version 3, commercial license available

commercial

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++

C++

Prolog, Rust

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

BSD
Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

hosted

Linux

Data scheme

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

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

integer and binary

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

yes

with tags

yes

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language

SQL-like query language (RQL)

yes

SQL-like query language (WOQL)

APIs and other access methods

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

HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

CLI Client
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

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

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

JavaScript (Node.js)
Python

JavaScript
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

consistent hashing

Sharding

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication with selectable replication factor

Multi-source replication

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

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

Cryptographically strong user authentication and audit trail

Authorization levels configured per client per database

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

Role-based access control

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.