DBMS > Amazon Redshift vs. Cassandra vs. Lovefield vs. Realm vs. SQLite

System Properties Comparison Amazon Redshift vs. Cassandra vs. Lovefield vs. Realm vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

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

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/redshift

cassandra.apache.org

google.github.io/lovefield

realm.io

www.sqlite.org

Technical documentation

docs.aws.amazon.com/redshift

cassandra.apache.org/doc/latest

github.com/google/lovefield/blob/master/docs/spec_index.md

realm.io/docs

www.sqlite.org/docs.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

Realm, acquired by MongoDB in May 2019

Dwayne Richard Hipp

Initial release

2012

2008

2014

2000

Current release

4.1.3, July 2023

2.1.12, February 2017

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Public Domain

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

JavaScript

Server operating systems

hosted

BSD
Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Android
Backend: server-less
iOS
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

does not fully support an SQL-standard

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

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

Proprietary protocol

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

JavaScript

.Net
Java

with Android only
Objective-C
React Native
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Using read-only observers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Representation of geographical distribution of servers is possible

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

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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