DBMS > Kinetica vs. Kyligence Enterprise vs. Snowflake vs. Valentina Server

System Properties Comparison Kinetica vs. Kyligence Enterprise vs. Snowflake vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

A distributed analytics engine for big data, built on top of Apache Kylin

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

Object-relational database and reports server

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.kinetica.com

kyligence.io/kyligence-enterprise

www.snowflake.com

www.valentina-db.net

Technical documentation

docs.kinetica.com

docs.snowflake.net/manuals/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Kinetica

Kyligence, Inc.

Snowflake Computing Inc.

Paradigma Software

Initial release

2012

2016

2014

1999

Current release

7.1, August 2021

5.7.5

License

Commercial or Open Source

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

C, C++

Java

Server operating systems

Linux

hosted

Linux
OS X
Windows

Data scheme

yes

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

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

SQL-like DML and DDL statements

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

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

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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 or Eventual Consistency depending on configuration

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

User concepts

Access control

Access rights for users and roles on table level

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

fine grained access rights according to SQL-standard

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