DBMS > Amazon Redshift vs. Apache Cassandra vs. JaguarDB vs. Snowflake

System Properties Comparison Amazon Redshift vs. Apache Cassandra vs. JaguarDB vs. Snowflake

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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

Performant, highly scalable DBMS for AI and IoT applications

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Wide column store

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

aws.amazon.com/redshift

cassandra.apache.org

www.jaguardb.com

www.snowflake.com

Technical documentation

docs.aws.amazon.com/redshift

cassandra.apache.org/doc/latest

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top level project, originally developped by Facebook

DataJaguar, Inc.

Snowflake Computing Inc.

Initial release

2012

2008

2015

2014

Current release

5.0-rc1, July 2024

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

GPL V3.0

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

C++

the server part. Clients available in other languages

Server operating systems

hosted

BSD
Linux
OS X
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

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)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol

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

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

yes

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

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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

Apache 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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