DBMS > AlaSQL vs. Hazelcast vs. Linter vs. MySQL vs. OrientDB

System Properties Comparison AlaSQL vs. Hazelcast vs. Linter vs. MySQL vs. OrientDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A widely adopted in-memory data grid

RDBMS for high security requirements

Widely used open source RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

Technical documentation

github.com/AlaSQL/alasql

hazelcast.org/imdg/docs

dev.mysql.com/doc

www.orientdb.com/docs/last/index.html

Developer

Andrey Gershun & Mathias R. Wulff

Hazelcast

relex.ru

Oracle

since 2010, originally MySQL AB, then Sun

OrientDB LTD; CallidusCloud; SAP

Initial release

2014

2008

1990

1995

2010

Current release

5.3.6, November 2023

8.4.0, April 2024

3.2.29, March 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

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Implementation language

JavaScript

Java

C and C++

Java

Server operating systems

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

All OS with a Java VM

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

Typing

predefined data types such as float or date

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

SQL

Support of SQL

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

SQL-like query language

yes

with proprietary extensions

SQL-like query language, no joins

APIs and other access methods

JavaScript API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC
Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

JavaScript

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

proprietary syntax

Java, Javascript

Triggers

yes

Events

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationship in graphs

Transaction concepts

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

yes

only for local storage and DOM-storage

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

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

Role-based access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles; record level security configurable

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