DBMS > Amazon Redshift vs. Microsoft Azure SQL Database vs. RethinkDB vs. SingleStore

System Properties Comparison Amazon Redshift vs. Microsoft Azure SQL Database vs. RethinkDB vs. SingleStore

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Database as a Service offering with high compatibility to Microsoft SQL Server

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Website

aws.amazon.com/redshift

azure.microsoft.com/en-us/products/azure-sql/database

rethinkdb.com

www.singlestore.com

Technical documentation

docs.aws.amazon.com/redshift

docs.microsoft.com/en-us/azure/azure-sql

rethinkdb.com/docs

docs.singlestore.com

Developer

Amazon (based on PostgreSQL)

Microsoft

The Linux Foundation

since July 2017

SingleStore Inc.

Initial release

2012

2010

2009

2013

Current release

V12

2.4.1, August 2020

8.5, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

free developer edition 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++

C++, Go

Server operating systems

hosted

Linux
OS X
Windows

Linux

64 bit version required

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

but no triggers and foreign keys

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

yes

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

yes

users and table-level permissions

Fine grained access control via users, groups and roles

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