DBMS > Amazon Redshift vs. Apache Doris vs. Apache Impala vs. Infobright vs. Microsoft SQL Server

System Properties Comparison Amazon Redshift vs. Apache Doris vs. Apache Impala vs. Infobright vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An MPP-based analytics DBMS embracing the MySQL protocol

Analytic DBMS for Hadoop

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

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

aws.amazon.com/redshift

doris.apache.org
github.com/apache/doris

impala.apache.org

ignitetech.com/softwarelibrary/infobrightdb

www.microsoft.com/en-us/sql-server

Technical documentation

docs.aws.amazon.com/redshift

github.com/apache/doris/wiki

impala.apache.org/impala-docs.html

learn.microsoft.com/en-US/sql/sql-server

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

Initial release

2012

2017

2013

2005

1989

Current release

1.2.2, February 2023

4.1.0, June 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2

commercial

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

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

hosted

Linux

Linux
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.

yes

Secondary indexes

restricted

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

All languages supporting JDBC/ODBC

Java

All languages supporting JDBC/ODBC

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

user defined functions and integration of map-reduce

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

Source-replica replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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