DBMS > Amazon Aurora vs. Amazon Redshift vs. Cassandra vs. Firebase Realtime Database vs. XTDB

System Properties Comparison Amazon Aurora vs. Amazon Redshift vs. Cassandra vs. Firebase Realtime Database vs. XTDB

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Large scale data warehouse service for use with business intelligence tools

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Wide column store

Document store

Secondary database models

Document store

Vector DBMS

starting with release V5

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

aws.amazon.com/rds/aurora

aws.amazon.com/redshift

cassandra.apache.org

firebase.google.com/products/realtime-database

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.aws.amazon.com/redshift

cassandra.apache.org/doc/latest

firebase.google.com/docs/database

www.xtdb.com/docs

Developer

Amazon

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

acquired by Google 2014

Juxt Ltd.

Initial release

2015

2012

2008

2012

2019

Current release

4.1.3, July 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Clojure

Server operating systems

hosted

BSD
Linux
OS X
Windows

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

Proprietary protocol

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

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Java
JavaScript
Objective-C

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions

in Python

limited functionality with using 'rules'

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

Representation of geographical distribution of servers is possible

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

yes, based on authentication and database rules

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.
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Licensing and pricing models

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