DBMS > GeoMesa vs. Hyprcubd vs. Microsoft Azure AI Search vs. PostGIS vs. SwayDB

System Properties Comparison GeoMesa vs. Hyprcubd vs. Microsoft Azure AI Search vs. PostGIS vs. SwayDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Serverless Time Series DBMS

Search-as-a-service for web and mobile app development

Spatial extension of PostgreSQL

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Vector DBMS

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

www.geomesa.org

hyprcubd.com (offline)

azure.microsoft.com/en-us/services/search

postgis.net

swaydb.simer.au

Technical documentation

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

learn.microsoft.com/en-us/azure/search

postgis.net/documentation

Developer

CCRi and others

Hyprcubd, Inc.

Microsoft

Simer Plaha

Initial release

2014

2015

2005

2018

Current release

5.0.0, May 2024

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

GPL v2.0

Open Source

GNU Affero GPL V3.0

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

Server operating systems

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC (https)

RESTful HTTP API

Supported programming languages

C#
Java
JavaScript
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Implicit feature of the cloud service

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

Implicit feature of the cloud service

yes

based on PostgreSQL

none

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

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

User concepts

Access control

yes

depending on the DBMS used for storage

token access

yes

using Azure authentication

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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