DBMS > 4D vs. GeoMesa vs. Snowflake

System Properties Comparison 4D vs. GeoMesa vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

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

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.4d.com

www.geomesa.org

www.snowflake.com

Technical documentation

developer.4d.com

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

docs.snowflake.net/manuals/index.html

Developer

4D, Inc

CCRi and others

Snowflake Computing Inc.

Initial release

1984

2014

Current release

v20, April 2023

4.0.5, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

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

Scala

Server operating systems

OS X
Windows

hosted

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

CLI Client
JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

depending on storage layer

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

User concepts

Access control

Users and groups

yes

depending on the DBMS used for storage

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

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