DBMS > Amazon Redshift vs. Amazon SimpleDB vs. HBase vs. jBASE vs. STSdb

System Properties Comparison Amazon Redshift vs. Amazon SimpleDB vs. HBase vs. jBASE vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

A robust multi-value DBMS comprising development tools and middleware

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

aws.amazon.com/redshift

aws.amazon.com/simpledb

hbase.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

github.com/STSSoft/STSdb4

Technical documentation

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

hbase.apache.org/book.html

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Amazon (based on PostgreSQL)

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Rocket Software (formerly Zumasys)

STS Soft SC

Initial release

2012

2007

2008

1991

2011

Current release

2.3.4, January 2021

5.7

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

GPLv2, commercial license available

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.

Implementation language

Java

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

AIX
Linux
Windows

Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

optional

yes

primitive types and user defined types (classes)

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

yes

All columns are indexed automatically

SQL

Support of SQL

yes

does not fully support an SQL-standard

Embedded SQL for jBASE in BASIC

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
Basic
Jabbascript
Java

C#
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Coprocessors in Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

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 specified for read operations

Immediate Consistency or Eventual Consistency

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

Concurrent data updates can be detected by the application

Single row ACID (across millions of columns)

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights can be defined down to the item level

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