DBMS > GeoMesa vs. Google Cloud Firestore vs. Microsoft SQL Server vs. PostGIS vs. TerarkDB

System Properties Comparison GeoMesa vs. Google Cloud Firestore vs. Microsoft SQL Server vs. PostGIS vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Microsofts flagship relational DBMS

Spatial extension of PostgreSQL

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	23.90
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

www.geomesa.org

firebase.google.com/products/firestore

www.microsoft.com/en-us/sql-server

postgis.net

github.com/bytedance/terarkdb

Technical documentation

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

firebase.google.com/docs/firestore

learn.microsoft.com/en-US/sql/sql-server

postgis.net/documentation

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

CCRi and others

Google

Microsoft

ByteDance, originally Terark

Initial release

2014

2017

1989

2005

2016

Current release

4.0.5, February 2024

SQL Server 2022, November 2022

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

restricted free version is available

Open Source

GPL v2.0

commercial

restricted open source version available

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

C++

Server operating systems

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

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

SQL

Support of SQL

yes

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

C++ API
Java API

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C++
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication

yes, but depending on the SQL-Server Edition

yes

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

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

yes

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

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