DBMS > AlaSQL vs. GeoMesa vs. Hazelcast vs. Snowflake

System Properties Comparison AlaSQL vs. GeoMesa vs. Hazelcast vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A widely adopted in-memory data grid

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Relational DBMS

Spatial DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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	0.78
Rank	#213	Overall
	#4	Spatial DBMS

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

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

hazelcast.org/imdg/docs

docs.snowflake.net/manuals/index.html

Developer

Andrey Gershun & Mathias R. Wulff

CCRi and others

Hazelcast

Snowflake Computing Inc.

Initial release

2014

2008

2014

Current release

4.0.5, February 2024

5.3.6, November 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache License 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

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

Scala

Java

Server operating systems

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

All OS with a Java VM

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

APIs and other access methods

JavaScript API

JCache
JPA
Memcached protocol
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

JavaScript

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions

Triggers

yes

Events

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

yes

Replicated Map

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on storage layer

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Concurrency

Support for concurrent manipulation of data

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Role-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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