DBMS > Elasticsearch vs. GeoMesa vs. Microsoft Azure Cosmos DB vs. PostGIS

System Properties Comparison Elasticsearch vs. GeoMesa vs. Microsoft Azure Cosmos DB vs. PostGIS

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Globally distributed, horizontally scalable, multi-model database service

Spatial extension of PostgreSQL

Primary database model

Search engine

Spatial DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Spatial DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS

Relational DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

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

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.elastic.co/elasticsearch

www.geomesa.org

azure.microsoft.com/services/cosmos-db

postgis.net

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

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

learn.microsoft.com/azure/cosmos-db

postgis.net/documentation

Developer

Elastic

CCRi and others

Microsoft

Initial release

2010

2014

2005

Current release

8.6, January 2023

5.0.0, May 2024

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache License 2.0

commercial

Open Source

GPL v2.0

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

Server operating systems

All OS with a Java VM

hosted

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

yes

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

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

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

Triggers

yes

by using the 'percolation' feature

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

Implicit feature of the cloud service

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

yes

Implicit feature of the cloud service

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

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.

Memcached and Redis integration

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights can be defined down to the item level

yes

based on PostgreSQL

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