DBMS > Amazon SimpleDB vs. Apache Phoenix vs. Cassandra vs. EXASOL

System Properties Comparison Amazon SimpleDB vs. Apache Phoenix vs. Cassandra vs. EXASOL

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Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Website

aws.amazon.com/simpledb

phoenix.apache.org

cassandra.apache.org

www.exasol.com

Technical documentation

docs.aws.amazon.com/simpledb

phoenix.apache.org

cassandra.apache.org/doc/latest

www.exasol.com/resources

Developer

Amazon

Apache Software Foundation

Apache top level project, originally developped by Facebook

Exasol

Initial release

2007

2014

2008

2000

Current release

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

4.1.3, July 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2

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

Server operating systems

hosted

Linux
Unix
Windows

BSD
Linux
OS X
Windows

Data scheme

schema-free

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

yes

All columns are indexed automatically

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

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

yes

APIs and other access methods

RESTful HTTP API

JDBC

Proprietary protocol

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

.Net
JDBC
ODBC
WebSocket

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

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

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Java
Lua
Python
R

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Access rights for users, groups and roles according to SQL-standard

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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