DBMS > Faircom EDGE vs. IRONdb vs. OrientDB vs. OrigoDB vs. SpatiaLite

System Properties Comparison Faircom EDGE vs. IRONdb vs. OrientDB vs. OrigoDB vs. SpatiaLite

Editorial information provided by DB-Engines

Name

IRONdb 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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Multi-model DBMS (Document, Graph, Key/Value)

A fully ACID in-memory object graph database

Spatial extension of SQLite

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store

Document store
Object oriented DBMS

Spatial DBMS

Secondary database models

Relational 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	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.faircom.com/products/faircom-edge

www.circonus.com/solutions/time-series-database/

orientdb.org

origodb.com

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

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

docs.circonus.com/irondb/category/getting-started

www.orientdb.com/docs/last/index.html

origodb.com/docs

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

FairCom Corporation

Circonus LLC.

OrientDB LTD; CallidusCloud; SAP

Robert Friberg et al

Alessandro Furieri

Initial release

1979

2017

2010

2009

under the name LiveDB

2008

Current release

V3, October 2020

V0.10.20, January 2018

3.2.29, March 2024

5.0.0, August 2020

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache version 2

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

C and C++

Java

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux

All OS with a Java JDK (>= JDK 6)

Linux
Windows

server-less

Data scheme

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

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

text, numeric, histograms

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like query language, no joins

yes

APIs and other access methods

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

HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

.NET Client API
HTTP API
LINQ

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

.Net

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes, in Lua

Java, Javascript

yes

Triggers

yes

Hooks

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Automatic, metric affinity per node

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

configurable replication factor, datacenter aware

Multi-source replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

when using SQL

yes

relationship in graphs

depending on model

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

Durability

Support for making data persistent

yes

Write ahead log

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.

Access rights for users and roles; record level security configurable

Role based authorization

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