DBMS > atoti vs. GeoMesa vs. Microsoft Azure Synapse Analytics vs. MonetDB

System Properties Comparison atoti vs. GeoMesa vs. Microsoft Azure Synapse Analytics vs. MonetDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A relational database management system that stores data in columns

Primary database model

Object oriented DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Website

atoti.io

www.geomesa.org

azure.microsoft.com/services/synapse-analytics

www.monetdb.org

Technical documentation

docs.atoti.io

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

docs.microsoft.com/azure/synapse-analytics

www.monetdb.org/Documentation

Developer

ActiveViam

CCRi and others

Microsoft

MonetDB BV

Initial release

2014

2016

2004

Current release

4.0.5, February 2024

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache License 2.0

commercial

Open Source

Mozilla Public License 2.0

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

Java

Scala

C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

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

Multidimensional Expressions (MDX)

yes

SQL 2003 with some extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

C#
Java
PHP

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

Server-side scripts

Stored procedures

Python

Transact SQL

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

depending on storage layer

Sharding, horizontal partitioning

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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.

yes

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

yes

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
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