DBMS > AlaSQL vs. Faircom EDGE vs. Hazelcast vs. HugeGraph vs. MySQL

System Properties Comparison AlaSQL vs. Faircom EDGE vs. Hazelcast vs. HugeGraph vs. MySQL

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 widely adopted in-memory data grid

A fast-speed and highly-scalable Graph DBMS

Widely used open source RDBMS

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Key-value store

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

alasql.org

www.faircom.com/products/faircom-edge

hazelcast.com

github.com/hugegraph
hugegraph.apache.org

www.mysql.com

Technical documentation

github.com/AlaSQL/alasql

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

hazelcast.org/imdg/docs

hugegraph.apache.org/docs

dev.mysql.com/doc

Developer

Andrey Gershun & Mathias R. Wulff

FairCom Corporation

Hazelcast

Baidu

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2014

1979

2008

2018

1995

Current release

V3, October 2020

5.3.6, November 2023

0.9

8.4.0, April 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

Restricted, free version available

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

ANSI C, C++

Java

C and C++

Server operating systems

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

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

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

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

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

yes

ANSI SQL queries

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JavaScript API

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

JCache
JPA
Memcached protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

JavaScript

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

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

Groovy
Java
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Event Listeners, Executor Services

asynchronous Gremlin script jobs

yes

proprietary syntax

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Replicated Map

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

edges in graph

yes

not for MyISAM storage engine

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

table locks or row locks depending on storage engine

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

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

Role-based access control

Users, roles and permissions

Users with fine-grained authorization concept

no user groups or roles

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