DBMS > Geode vs. GeoMesa vs. Linter vs. Microsoft Azure Cosmos DB

System Properties Comparison Geode vs. GeoMesa vs. Linter vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

RDBMS for high security requirements

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Key-value store

Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

geode.apache.org

www.geomesa.org

linter.ru

azure.microsoft.com/services/cosmos-db

Technical documentation

geode.apache.org/docs

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

learn.microsoft.com/azure/cosmos-db

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

CCRi and others

relex.ru

Microsoft

Initial release

2002

2014

1990

2014

Current release

1.1, February 2017

4.0.5, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

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

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Implementation language

Java

Scala

C and C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

SQL

Support of SQL

SQL-like query language (OQL)

yes

SQL-like query language

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

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

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

JavaScript

Triggers

yes

Cache Event Listeners

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

depending on storage layer

Source-replica replication

yes

Implicit feature of the cloud service

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

Eventual Consistency

depending on storage layer

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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.

yes

depending on storage layer

User concepts

Access control

Access rights per client and object definable

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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