DBMS > Kinetica vs. Microsoft SQL Server vs. OushuDB vs. Percona Server for MongoDB vs. Snowflake

System Properties Comparison Kinetica vs. Microsoft SQL Server vs. OushuDB vs. Percona Server for MongoDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Microsofts flagship relational DBMS

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.kinetica.com

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

www.oushu.com/product/oushuDB

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

www.snowflake.com

Technical documentation

docs.kinetica.com

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

www.oushu.com/documentation

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

docs.snowflake.net/manuals/index.html

Developer

Kinetica

Microsoft

Oushu

Percona

Snowflake Computing Inc.

Initial release

2012

1989

2015

2014

Current release

7.1, August 2021

SQL Server 2022, November 2022

4.0.1, August 2020

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

restricted free version is available

commercial

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.

SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

C, C++

C++

Server operating systems

Linux

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

SQL-like DML and DDL statements

yes

Full-featured ANSI SQL support

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

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

C
C++

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

user defined functions

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

yes

JavaScript

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

GPU vRAM or System RAM

yes

via In-Memory Engine

User concepts

Access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

Access rights for users and roles

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.