DBMS > AlaSQL vs. Citus vs. GeoMesa vs. Hazelcast vs. MySQL

System Properties Comparison AlaSQL vs. Citus vs. GeoMesa vs. Hazelcast vs. MySQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A widely adopted in-memory data grid

Widely used open source RDBMS

Primary database model

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

Score	2.15
Rank	#123	Overall
	#60	Relational DBMS

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

docs.citusdata.com

www.geomesa.org/documentation/stable/user/index.html

hazelcast.org/imdg/docs

dev.mysql.com/doc

Developer

Andrey Gershun & Mathias R. Wulff

CCRi and others

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2014

2010

2014

2008

1995

Current release

8.1, December 2018

4.0.5, February 2024

5.3.6, November 2023

8.3.0, January 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

AGPL, commercial license also available

Open Source

Apache License 2.0

Open Source

Apache Version 2; commercial licenses available

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

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

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Implementation language

JavaScript

Scala

Java

C and C++

Server operating systems

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

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

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

specific XML type available, but no XML query functionality

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.

yes

standard, with numerous extensions

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JavaScript API

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

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

JavaScript

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

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

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

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Event Listeners, Executor Services

yes

proprietary syntax

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

depending on storage layer

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

depending on storage layer

yes

Replicated Map

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

depending on storage layer

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

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

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

depending on storage layer

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

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