DBMS > Linter vs. Snowflake vs. Spark SQL vs. STSdb vs. SWC-DB

System Properties Comparison Linter vs. Snowflake vs. Spark SQL vs. STSdb vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

RDBMS for high security requirements

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store

Wide column store

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

linter.ru

www.snowflake.com

spark.apache.org/sql

github.com/STSSoft/STSdb4

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.snowflake.net/manuals/index.html

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

Developer

relex.ru

Snowflake Computing Inc.

Apache Software Foundation

STS Soft SC

Alex Kashirin

Initial release

1990

2014

2011

2020

Current release

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Open Source

GPL V3

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 and C++

Scala

C++

Server operating systems

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

hosted

Linux
OS X
Windows

Windows

Linux

Data scheme

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

yes

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

CLI Client
JDBC
ODBC

JDBC
ODBC

.NET Client API

Proprietary protocol
Thrift

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

JavaScript (Node.js)
Python

Java
Python
R
Scala

C#
Java

C++

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

yes

yes, utilizing Spark Core

none

Sharding

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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.