DBMS > Google Cloud Firestore vs. Microsoft Azure SQL Database vs. SwayDB vs. TinkerGraph

System Properties Comparison Google Cloud Firestore vs. Microsoft Azure SQL Database vs. SwayDB vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

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.

Database as a Service offering with high compatibility to Microsoft SQL Server

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Score	0.08
Rank	#345	Overall
	#34	Graph DBMS

Website

firebase.google.com/products/firestore

azure.microsoft.com/en-us/products/azure-sql/database

swaydb.simer.au

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

firebase.google.com/docs/firestore

docs.microsoft.com/en-us/azure/azure-sql

Developer

Google

Microsoft

Simer Plaha

Initial release

2017

2010

2018

2009

Current release

V12

License

Commercial or Open Source

commercial

Open Source

GNU Affero GPL V3.0

Open Source

Apache 2.0

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

C++

Scala

Java

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.

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

TinkerPop 3

Supported programming languages

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
Kotlin
Scala

Groovy
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Transact SQL

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, with always 3 replicas available

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

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, 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

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