DBMS > Amazon Redshift vs. Apache Phoenix vs. Cassandra vs. VoltDB

System Properties Comparison Amazon Redshift vs. Apache Phoenix vs. Cassandra vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A scale-out RDBMS with evolutionary schema built on Apache HBase

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Wide column store

Relational DBMS

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	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

aws.amazon.com/redshift

phoenix.apache.org

cassandra.apache.org

www.voltdb.com

Technical documentation

docs.aws.amazon.com/redshift

phoenix.apache.org

cassandra.apache.org/doc/latest

docs.voltdb.com

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top level project, originally developped by Facebook

VoltDB Inc.

Initial release

2012

2014

2008

2010

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

4.1.3, July 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

hosted

Linux
Unix
Windows

BSD
Linux
OS X
Windows

Linux
OS X

for development

Data scheme

yes

late-bound, schema-on-read capabilities

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

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

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

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

JDBC

Proprietary protocol

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights for users can be defined per object

Users and roles with access to stored procedures

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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