DBMS > Google Cloud Firestore vs. Microsoft Azure Cosmos DB vs. Trafodion vs. TypeDB

System Properties Comparison Google Cloud Firestore vs. Microsoft Azure Cosmos DB vs. Trafodion vs. TypeDB

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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.

Globally distributed, horizontally scalable, multi-model database service

Transactional SQL-on-Hadoop DBMS

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Spatial DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

firebase.google.com/products/firestore

azure.microsoft.com/services/cosmos-db

trafodion.apache.org

typedb.com

Technical documentation

firebase.google.com/docs/firestore

learn.microsoft.com/azure/cosmos-db

trafodion.apache.org/documentation.html

typedb.com/docs

Developer

Google

Microsoft

Apache Software Foundation, originally developed by HP

Vaticle

Initial release

2017

2014

2016

Current release

2.3.0, February 2019

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL Version 3, commercial licenses 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

C++, Java

Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

All languages supporting JDBC/ODBC/ADO.Net

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

JavaScript

Java Stored Procedures

Triggers

yes, with Cloud Functions

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

yes, via HBase

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

via user defined functions and HBase

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

substituted by the relationship feature

Transaction concepts

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

yes

Multi-item ACID transactions with snapshot isolation within a partition

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.

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.

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Licensing and pricing models

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