DBMS > MySQL vs. Snowflake vs. Spark SQL vs. SQL.JS vs. VoltDB

System Properties Comparison MySQL vs. Snowflake vs. Spark SQL vs. SQL.JS vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

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

Port of SQLite to JavaScript

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

Technical documentation

dev.mysql.com/doc

docs.snowflake.net/manuals/index.html

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

sql.js.org/documentation/index.html

docs.voltdb.com

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Snowflake Computing Inc.

Apache Software Foundation

Alon Zakai

enhancements implemented by others

VoltDB Inc.

Initial release

1995

2014

2012

2010

Current release

8.4.0, April 2024

3.5.0 ( 2.13), September 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Scala

JavaScript

Java, C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

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

Linux
OS X

for development

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

yes

with proprietary extensions

yes

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

CLI Client
JDBC
ODBC

JDBC
ODBC

JavaScript API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript (Node.js)
Python

Java
Python
R
Scala

JavaScript

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

user defined functions

Java

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

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

Users and roles with access to stored procedures

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