DBMS > AlaSQL vs. Kinetica vs. SiteWhere vs. Snowflake vs. Spark SQL

System Properties Comparison AlaSQL vs. Kinetica vs. SiteWhere vs. Snowflake vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Fully vectorized database across both GPUs and CPUs

M2M integration platform for persisting/querying time series data

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Relational DBMS

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	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

alasql.org

www.kinetica.com

github.com/sitewhere/sitewhere

www.snowflake.com

spark.apache.org/sql

Technical documentation

github.com/AlaSQL/alasql

docs.kinetica.com

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Andrey Gershun & Mathias R. Wulff

Kinetica

SiteWhere

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2014

2012

2010

2014

Current release

7.1, August 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C, C++

Java

Scala

Server operating systems

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

Linux

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

predefined 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

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like DML and DDL statements

yes

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

JDBC
ODBC
RESTful HTTP API

HTTP REST

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

JavaScript

C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

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

none

Sharding

based on HBase

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

based on HBase

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Users with fine-grained authorization concept

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

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