DBMS > Amazon DocumentDB vs. GeoMesa vs. Google Cloud Firestore

System Properties Comparison Amazon DocumentDB vs. GeoMesa vs. Google Cloud Firestore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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.

Primary database model

Document store

Spatial DBMS

Document store

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

Score	1.89
Rank	#137	Overall
	#24	Document stores

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Website

aws.amazon.com/documentdb

www.geomesa.org

firebase.google.com/products/firestore

Technical documentation

aws.amazon.com/documentdb/resources

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

firebase.google.com/docs/firestore

Developer

CCRi and others

Google

Initial release

2019

2014

2017

Current release

4.0.5, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

commercial

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

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.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

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

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

depending on storage layer

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

yes

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

User concepts

Access control

Access rights for users and roles

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.

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

Mask sensitive Amazon DocumentDB log data with Amazon CloudWatch Logs data protection | Amazon Web Services
16 April 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

Run complex queries on massive amounts of data stored on your Amazon DocumentDB clusters using Apache Spark ...
10 April 2024, AWS Blog

Achieve continuous delivery with blue/green deployments using Amazon DocumentDB database cloning and AWS ...
27 March 2024, AWS Blog

provided by Google News

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google’s Firebase gets AI extensions, opens up its marketplace
10 May 2023, TechCrunch

Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Essentials for Working With Firestore in Python | by Lynn G. Kwong
13 November 2022, Towards Data Science

provided by Google News

Share this page