DBMS > Kinetica vs. Sequoiadb vs. SiteWhere vs. Snowflake

System Properties Comparison Kinetica vs. Sequoiadb vs. SiteWhere vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

NewSQL database with distributed OLTP and SQL

M2M integration platform for persisting/querying time series data

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

Primary database model

Relational DBMS

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	0.48
Rank	#260	Overall
	#41	Document stores
	#121	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

www.kinetica.com

www.sequoiadb.com

github.com/sitewhere/sitewhere

www.snowflake.com

Technical documentation

docs.kinetica.com

www.sequoiadb.com/en/index.php?m=Files&a=index

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

Developer

Kinetica

Sequoiadb Ltd.

SiteWhere

Snowflake Computing Inc.

Initial release

2012

2013

2010

2014

Current release

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

Common Public Attribution License Version 1.0

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++

C++

Java

Server operating systems

Linux

Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

predefined scheme

yes

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

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

.Net
C++
Java
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

user defined functions

Triggers

yes

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

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on HBase

yes

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Document is locked during a transaction

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

User concepts

Access control

Access rights for users and roles on table level

simple password-based access control

Users with fine-grained authorization concept

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

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