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

System Properties Comparison Amazon Redshift vs. DataFS vs. Microsoft Azure SQL Database 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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

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

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

Document store
Graph 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	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Website

aws.amazon.com/redshift

newdatabase.com

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

www.singlestore.com

Technical documentation

docs.aws.amazon.com/redshift

dev.mobiland.com/Overview.xsp

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

docs.singlestore.com

Developer

Amazon (based on PostgreSQL)

Mobiland AG

Microsoft

SingleStore Inc.

Initial release

2012

2018

2010

2013

Current release

1.1.263, October 2022

V12

8.5, January 2024

License

Commercial or Open Source

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

Windows

hosted

Linux

64 bit version required

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

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

.NET Client API
Proprietary client DLL
WinRT client

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
C#
C++
VB.Net

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

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

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

yes

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

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

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

Concurrency

Support for concurrent manipulation of data

yes

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

Windows-Profile

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

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