DBMS > Amazon Redshift vs. Infobright vs. OpenMLDB vs. Sadas Engine

System Properties Comparison Amazon Redshift vs. Infobright vs. OpenMLDB vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

An open-source machine learning database that provides a feature platform for training and inference

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

aws.amazon.com/redshift

ignitetech.com/softwarelibrary/infobrightdb

openmldb.ai

www.sadasengine.com

Technical documentation

docs.aws.amazon.com/redshift

openmldb.ai/docs/zh/main

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Amazon (based on PostgreSQL)

Ignite Technologies Inc.; formerly InfoBright Inc.

4 Paradigm Inc.

SADAS s.r.l.

Initial release

2012

2005

2020

2006

Current release

2024-2 February 2024

8.0

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

commercial

free trial version 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

C++, Java, Scala

C++

Server operating systems

hosted

Linux
Windows

Linux

AIX
Linux
Windows

Data scheme

yes

Fixed schema

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
SQLAlchemy

JDBC
ODBC
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Go
Java
Python
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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

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