DBMS > Altibase vs. Amazon Redshift vs. HEAVY.AI vs. mSQL

System Properties Comparison Altibase vs. Amazon Redshift vs. HEAVY.AI vs. mSQL

Please select another system to include it in the comparison.

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Website

altibase.com

aws.amazon.com/redshift

github.com/heavyai/heavydb
www.heavy.ai

hughestech.com.au/products/msql

Technical documentation

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

docs.aws.amazon.com/redshift

docs.heavy.ai

Developer

Altibase

Amazon (based on PostgreSQL)

HEAVY.AI, Inc.

Hughes Technologies

Initial release

1999

2012

2016

1994

Current release

v7.3, 2023, August 2023

5.10, January 2022

4.4, October 2021

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

free licenses can be provided

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++

C++ and CUDA

Server operating systems

AIX
HP-UX
Linux

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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

restricted

yes

SQL

Support of SQL

ANSI SQL-92

yes

does not fully support an SQL-standard

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

JDBC
ODBC

Supported programming languages

C
C++
Java

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.