DBMS > Amazon DynamoDB vs. Google Cloud Firestore vs. GridGain

System Properties Comparison Amazon DynamoDB vs. Google Cloud Firestore vs. GridGain

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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.

GridGain is an in-memory computing platform, built on Apache Ignite

Primary database model

Document store
Key-value store

Document store

Columnar
Key-value store
Object Oriented DBMS
Relational DBMS

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

Score	70.95
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	6.75
Rank	#54	Overall
	#9	Document stores

Score	1.44
Rank	#152	Overall
	#1	Columnar
	#26	Key-value stores
	#1	Object Oriented DBMS
	#70	Relational DBMS

Website

aws.amazon.com/dynamodb

firebase.google.com/products/firestore

www.gridgain.com

Technical documentation

docs.aws.amazon.com/dynamodb

firebase.google.com/docs/firestore

www.gridgain.com/docs/index.html

Developer

Amazon

Google

GridGain Systems, Inc.

Initial release

2012

2017

2007

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

commercial, open source

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, C++, .Net, Python, REST, SQL

Server operating systems

hosted

Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

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

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

RESTful HTTP API

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

by integration with AWS Lambda

yes, with Cloud Functions

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Using Cloud Dataflow

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

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.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Role-based access control
Security Hooks for custom implementations

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