DBMS > Kinetica vs. OpenQM vs. Snowflake vs. SQL.JS

System Properties Comparison Kinetica vs. OpenQM vs. Snowflake vs. SQL.JS

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Multivalue DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

www.kinetica.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.snowflake.com

sql.js.org

Technical documentation

docs.kinetica.com

docs.snowflake.net/manuals/index.html

sql.js.org/documentation/index.html

Developer

Kinetica

Rocket Software, originally Martin Phillips

Snowflake Computing Inc.

Alon Zakai

enhancements implemented by others

Initial release

2012

1993

2014

2012

Current release

7.1, August 2021

3.4-12

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

commercial

Open Source

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++

JavaScript

Server operating systems

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

with some exceptions

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

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

JavaScript API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

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

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

none

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

except by serializing a db to a file

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

Access rights can be defined down to the item level

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

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