DBMS > GeoMesa vs. PostGIS vs. Quasardb vs. StarRocks

System Properties Comparison GeoMesa vs. PostGIS vs. Quasardb vs. StarRocks

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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.

Spatial extension of PostgreSQL

Distributed, high-performance timeseries database

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Spatial DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

Technical documentation

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

postgis.net/documentation

doc.quasar.ai/master

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

CCRi and others

quasardb

The Linux Foundation

since Feb 2023

Initial release

2014

2005

2009

2020

Current release

5.0.0, May 2024

3.4.2, February 2024

3.14.1, January 2024

2.5.3, March 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GPL v2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache Version 2.0

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

Scala

C++

C++, Java

Server operating systems

BSD
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

HTTP API

JDBC
MySQL protocol

Supported programming languages

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

yes

based on PostgreSQL

Sharding

consistent hashing

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

based on PostgreSQL

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

by using LevelDB

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

Transient mode

User concepts

Access control

yes

depending on the DBMS used for storage

yes

based on PostgreSQL

Cryptographically strong user authentication and audit trail

Role based access control and fine grained access rights

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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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