DBMS > Apache Cassandra vs. Fauna vs. Google Cloud Firestore

System Properties Comparison Apache Cassandra vs. Fauna vs. Google Cloud Firestore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

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

Wide column store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store

Secondary database models

Vector DBMS

starting with release V5

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

Score	97.61
Rank	#11	Overall
	#1	Wide column stores

Score	1.50
Rank	#147	Overall
	#26	Document stores
	#13	Graph DBMS
	#67	Relational DBMS
	#13	Time Series DBMS

Score	6.46
Rank	#54	Overall
	#9	Document stores

Website

cassandra.apache.org

fauna.com

firebase.google.com/products/firestore

Technical documentation

cassandra.apache.org/doc/latest

docs.fauna.com

firebase.google.com/docs/firestore

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Fauna, Inc.

Google

Initial release

2008

2014

2017

Current release

5.0-rc1, July 2024

License

Commercial or Open Source

Open Source

Apache version 2

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Scala

Server operating systems

BSD
Linux
OS X
Windows

hosted

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

RESTful HTTP API

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

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

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.

User concepts

Access control

Access rights for users can be defined per object

Identity management, authentication, and 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.

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Apache Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

How AI Agents and Humans Collaborate to Turn Unstructured Data into Action
24 October 2024

How to Support Streaming in AI Applications with LangChain and Langflow
22 October 2024

Building Knowledge Graphs at Production Scale for GenAI
16 October 2024

Exploring Video Search with OpenOrigins: Frame Search Versus Multi-Modal Embeddings
10 October 2024

GenAI in Retail: How to Build a Shopping Assistant with Langflow
7 October 2024

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.