DBMS > EsgynDB vs. Faircom EDGE vs. Lovefield vs. Newts

System Properties Comparison EsgynDB vs. Faircom EDGE vs. Lovefield vs. Newts

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Embeddable relational database for web apps written in pure JavaScript

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

www.esgyn.cn

www.faircom.com/products/faircom-edge

google.github.io/lovefield

opennms.github.io/newts

Technical documentation

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

github.com/google/lovefield/blob/master/docs/spec_index.md

github.com/OpenNMS/newts/wiki

Developer

Esgyn

FairCom Corporation

Google

OpenNMS Group

Initial release

2015

1979

2014

Current release

V3, October 2020

2.1.12, February 2017

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

ANSI C, C++

JavaScript

Java

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Data scheme

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

ADO.NET
JDBC
ODBC

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

HTTP REST
Java API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

JavaScript

Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

when using SQL

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

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

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