DBMS > Apache Kylin vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Percona Server for MongoDB vs. Snowflake

System Properties Comparison Apache Kylin vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Percona Server for MongoDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

Microsofts flagship relational DBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

kylin.apache.org

azure.microsoft.com/services/synapse-analytics

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

www.percona.com/mongodb/software/percona-server-for-mongodb

www.snowflake.com

Technical documentation

kylin.apache.org/docs

docs.microsoft.com/azure/synapse-analytics

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

docs.percona.com/percona-distribution-for-mongodb

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

Microsoft

Percona

Snowflake Computing Inc.

Initial release

2015

2016

1989

2015

2014

Current release

3.1.0, July 2020

SQL Server 2022, November 2022

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

GPL Version 2

commercial

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

Java

C++

Server operating systems

Linux

hosted

Linux
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

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

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

C#
Java
PHP

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Transact SQL

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

JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

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

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

via In-Memory Engine

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Access rights for users and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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