DBMS > Amazon DocumentDB vs. Google Cloud Firestore vs. Oracle Coherence

System Properties Comparison Amazon DocumentDB vs. Google Cloud Firestore vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

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

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.

Oracles in-memory data grid solution

Primary database model

Document store

Key-value store

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

Score	1.89
Rank	#137	Overall
	#24	Document stores

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Website

aws.amazon.com/documentdb

firebase.google.com/products/firestore

www.oracle.com/java/coherence

Technical documentation

aws.amazon.com/documentdb/resources

firebase.google.com/docs/firestore

docs.oracle.com/en/middleware/standalone/coherence

Developer

Google

Oracle

Initial release

2019

2017

2007

Current release

14.1, August 2023

License

Commercial or Open Source

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

Java

Server operating systems

hosted

All OS with a Java VM

Data scheme

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

JCache
JPA
RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

.Net
C++
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Triggers

yes, with Cloud Functions

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

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

Multi-source replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

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

authentification to access the cache via certificates or http basic authentication

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More resources

DB-Engines blog posts

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

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