DBMS > GeoMesa vs. Microsoft Azure Cosmos DB vs. MonetDB vs. QuestDB

System Properties Comparison GeoMesa vs. Microsoft Azure Cosmos DB vs. MonetDB vs. QuestDB

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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.

Globally distributed, horizontally scalable, multi-model database service

A relational database management system that stores data in columns

A high performance open source SQL database for time series data

Primary database model

Spatial DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Website

www.geomesa.org

azure.microsoft.com/services/cosmos-db

www.monetdb.org

questdb.io

Technical documentation

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

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

questdb.io/docs

Developer

CCRi and others

Microsoft

MonetDB BV

QuestDB Technology Inc

Initial release

2014

2004

2014

Current release

5.0.1, July 2024

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache 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

Scala

Java (Zero-GC), C++, Rust

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL 2003 with some extensions

SQL with time-series extensions

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

JavaScript

yes, in SQL, C, R

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Implicit feature of the cloud service

Sharding via remote tables

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

ACID for single-table writes

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

yes

through memory mapped files

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

More information provided by the system vendor

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