DBMS > Altibase vs. Amazon Redshift vs. Amazon SimpleDB vs. Axibase vs. HBase

System Properties Comparison Altibase vs. Amazon Redshift vs. Amazon SimpleDB vs. Axibase vs. HBase

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

Primary database model

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Website

altibase.com

aws.amazon.com/redshift

aws.amazon.com/simpledb

axibase.com/docs/atsd/finance

hbase.apache.org

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

hbase.apache.org/book.html

Developer

Altibase

Amazon (based on PostgreSQL)

Amazon

Axibase Corporation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

1999

2012

2007

2013

2008

Current release

v7.3, 2023, August 2023

15585

2.3.4, January 2021

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache version 2

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

C++

Java

Server operating systems

AIX
HP-UX
Linux

hosted

Linux

Linux
Unix
Windows

using Cygwin

Data scheme

yes

schema-free

yes

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

options to bring your own types, AVRO

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

restricted

yes

All columns are indexed automatically

SQL

Support of SQL

ANSI SQL-92

yes

does not fully support an SQL-standard

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

RESTful HTTP API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

Supported programming languages

C
C++
Java

All languages supporting JDBC/ODBC

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

Go
Java
PHP
Python
R
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in Python

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

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)

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

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