DBMS > Cassandra vs. etcd vs. Google Cloud Firestore vs. Realm

System Properties Comparison Cassandra vs. etcd vs. Google Cloud Firestore vs. Realm

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A distributed reliable key-value store

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.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Wide column store

Key-value store

Document store

Secondary database models

Vector DBMS

starting with release V5

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

cassandra.apache.org

etcd.io
github.com/etcd-io/etcd

firebase.google.com/products/firestore

realm.io

Technical documentation

cassandra.apache.org/doc/latest

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

firebase.google.com/docs/firestore

realm.io/docs

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

Realm, acquired by MongoDB in May 2019

Initial release

2008

2017

2014

Current release

4.1.3, July 2023

3.4, August 2019

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2.0

commercial

Open Source

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

Server operating systems

BSD
Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

hosted

Android
Backend: server-less
iOS
Windows

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.

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

gRPC
JSON over HTTP

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

runs within the applications so server-side scripts are unnecessary

Triggers

yes

yes, watching key changes

yes, with Cloud Functions

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication

none

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

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

In-Memory realm

User concepts

Access control

Access rights for users can be defined per object

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

yes

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

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...
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