DBMS > Elasticsearch vs. GeoMesa vs. PostGIS vs. WakandaDB

System Properties Comparison Elasticsearch vs. GeoMesa vs. PostGIS vs. WakandaDB

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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.

Spatial extension of PostgreSQL

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Search engine

Spatial DBMS

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS
Vector 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	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.elastic.co/elasticsearch

www.geomesa.org

postgis.net

wakanda.github.io

Technical documentation

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

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

postgis.net/documentation

wakanda.github.io/doc

Developer

Elastic

CCRi and others

Wakanda SAS

Initial release

2010

2014

2005

2012

Current release

8.6, January 2023

4.0.5, February 2024

3.4.2, February 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache License 2.0

Open Source

GPL v2.0

Open Source

AGPLv3, extended commercial license available

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

Java

Scala

C++, JavaScript

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Data scheme

schema-free

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

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

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

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

yes

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

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

Immediate Consistency

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.

Memcached and Redis integration

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

yes

based on PostgreSQL

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

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26 March 2024, insider.govtech.com

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29 April 2024, InfoQ.com

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