DBMS > Blueflood vs. Faircom EDGE vs. OrigoDB vs. SpatiaLite

System Properties Comparison Blueflood vs. Faircom EDGE vs. OrigoDB vs. SpatiaLite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

A fully ACID in-memory object graph database

Spatial extension of SQLite

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

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	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

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

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

blueflood.io

www.faircom.com/products/faircom-edge

origodb.com

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

Technical documentation

github.com/rax-maas/blueflood/wiki

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

origodb.com/docs

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

Developer

Rackspace

FairCom Corporation

Robert Friberg et al

Alessandro Furieri

Initial release

2013

1979

2009

under the name LiveDB

2008

Current release

V3, October 2020

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Restricted, free version available

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

Java

ANSI C, C++

C++

Server operating systems

Linux
OS X

Android
Linux

ARM, x86
Raspbian
Windows

Linux
Windows

server-less

Data scheme

predefined scheme

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

yes

APIs and other access methods

HTTP REST

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

.NET Client API
HTTP API
LINQ

Supported programming languages

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

.Net

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

File partitioning

Customizable business rules for partitioning

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

when using SQL

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.

Role based authorization

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

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

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

Winners of the 2021 IoT Evolution Product of the Year Awards Announced
6 July 2021, IoT Evolution World

Trend-Setting Products in Data and Information Management for 2023
8 December 2022, Database Trends and Applications

How To Collect, Store, and Query IoT Data With MQTT + SQL
16 June 2022, IoT For All

Trend-Setting Products in Data and Information Management for 2024
6 December 2023, Database Trends and Applications

provided by Google News

Share this page