DBMS > Dolt vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Netezza

System Properties Comparison Dolt vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Netezza

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Editorial information provided by DB-Engines

Name

Description

A MySQL compatible DBMS with Git-like versioning of data and schema

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

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	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

github.com/dolthub/dolt
www.dolthub.com

azure.microsoft.com/services/synapse-analytics

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

www.ibm.com/products/netezza

Technical documentation

docs.dolthub.com

docs.microsoft.com/azure/synapse-analytics

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

Developer

DoltHub Inc

Microsoft

IBM

Initial release

2018

2016

1989

2000

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
macOS
Windows

hosted

Linux
Windows

Linux

included in appliance

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

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
HTTP REST

ADO.NET
JDBC
ODBC

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

JDBC
ODBC
OLE DB

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
Java
PHP

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

currently in alpha release

Transact SQL

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

Only one user is configurable, and must be specified in the config file at startup

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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