DBMS > Faircom EDGE vs. KairosDB vs. RavenDB vs. STSdb vs. ToroDB

System Properties Comparison Faircom EDGE vs. KairosDB vs. RavenDB vs. STSdb vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Distributed Time Series DBMS based on Cassandra or H2

Open Source Operational and Transactional Enterprise NoSQL Document Database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Key-value store
Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
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	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.faircom.com/products/faircom-edge

github.com/kairosdb/kairosdb

ravendb.net

github.com/STSSoft/STSdb4

github.com/torodb/server

Technical documentation

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

kairosdb.github.io

ravendb.net/docs

Developer

FairCom Corporation

Hibernating Rhinos

STS Soft SC

8Kdata

Initial release

1979

2013

2010

2011

2016

Current release

V3, October 2020

1.2.2, November 2018

5.4, July 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

AGPL version 3, commercial license available

Open Source

GPLv2, commercial license available

Open Source

AGPL-V3

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

ANSI C, C++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

Windows

All OS with a Java 7 VM

Data scheme

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

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

primitive types and user defined types (classes)

yes

string, integer, double, boolean, date, object_id

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

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language (RQL)

APIs and other access methods

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

Graphite protocol
HTTP REST
Telnet 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

.NET Client API

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

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

C#
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

based on Cassandra

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

based on Cassandra

Multi-source replication

none

Source-replica replication

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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.

simple password-based access control

Authorization levels configured per client per database

Access rights for users and roles

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