DBMS > AlaSQL vs. Faircom EDGE vs. Graph Engine vs. Postgres-XL

System Properties Comparison AlaSQL vs. Faircom EDGE vs. Graph Engine vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	0.03
Rank	#380	Overall
	#59	Key-value stores
	#157	Relational DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

alasql.org

www.faircom.com/products/faircom-edge

www.graphengine.io

www.postgres-xl.org

Technical documentation

github.com/AlaSQL/alasql

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

www.graphengine.io/docs/manual

www.postgres-xl.org/documentation

Developer

Andrey Gershun & Mathias R. Wulff

FairCom Corporation

Microsoft

Initial release

2014

1979

2010

2014

since 2012, originally named StormDB

Current release

V3, October 2020

10 R1, October 2018

License

Commercial or Open Source

Open Source

MIT-License

commercial

Restricted, free version available

Open Source

MIT License

Open Source

Mozilla public license

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

JavaScript

ANSI C, C++

.NET and C

Server operating systems

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

Android
Linux

ARM, x86
Raspbian
Windows

.NET

Linux
macOS

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

ANSI SQL queries

yes

distributed, parallel query execution

APIs and other access methods

JavaScript API

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

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

JavaScript

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

C#
C++
F#
Visual Basic

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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.

fine grained access rights according to SQL-standard

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