DBMS > AlaSQL vs. Amazon DynamoDB vs. EsgynDB vs. Faircom EDGE

System Properties Comparison AlaSQL vs. Amazon DynamoDB vs. EsgynDB vs. Faircom EDGE

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Relational DBMS

Key-value store
Relational DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

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

Website

alasql.org

aws.amazon.com/dynamodb

www.esgyn.cn

www.faircom.com/products/faircom-edge

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/dynamodb

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

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

Esgyn

FairCom Corporation

Initial release

2014

2012

2015

1979

Current release

V3, October 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

free tier for a limited amount of database operations

commercial

Restricted, free version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++, Java

ANSI C, C++

Server operating systems

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

hosted

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

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

yes

ANSI SQL queries

APIs and other access methods

JavaScript API

RESTful HTTP API

ADO.NET
JDBC
ODBC

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

Supported programming languages

JavaScript

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

File partitioning

Customizable business rules for partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication between multi datacenters

yes

Synchronous and asynchronous realtime replication based on transaction logs

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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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