DBMS > GeoMesa vs. MonetDB vs. OushuDB

System Properties Comparison GeoMesa vs. MonetDB vs. OushuDB

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Editorial information provided by DB-Engines

Name

Description

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

A relational database management system that stores data in columns

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Spatial DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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Trend Chart

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	1.72
Rank	#148	Overall
	#68	Relational DBMS

Score	0.09
Rank	#357	Overall
	#154	Relational DBMS

Website

www.geomesa.org

www.monetdb.org

www.oushu.com/product/oushuDB

Technical documentation

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

www.monetdb.org/Documentation

www.oushu.com/documentation

Developer

CCRi and others

MonetDB BV

Oushu

Initial release

2014

2004

Current release

4.0.5, February 2024

Dec2023 (11.49), December 2023

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Mozilla Public License 2.0

commercial

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.

Implementation language

Scala

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

Full-featured ANSI SQL support

APIs and other access methods

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

Supported programming languages

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C++

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

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

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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More resources

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