DBMS > Spark SQL vs. VelocityDB

System Properties Comparison Spark SQL vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

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

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS
Object oriented DBMS

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

Score	20.07
Rank	#35	Overall
	#21	Relational DBMS

Score	0.19
Rank	#370	Overall
	#35	Graph DBMS
	#19	Object oriented DBMS

Website

spark.apache.org/sql

velocitydb.com

Technical documentation

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

velocitydb.com/UserGuide

Developer

Apache Software Foundation

VelocityDB Inc

Initial release

2014

2011

Current release

3.4.0 ( 2.13), April 2023

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Scala

Server operating systems

Linux
OS X
Windows

Any that supports .NET

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

.Net

Supported programming languages

Java
Python
R
Scala

.Net

Server-side scripts

Stored procedures

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

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.

yes

User concepts

Access control

Based on Windows Authentication

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More resources

Recent citations in the news

Big Data Processing with Apache Spark - Part 2: Spark SQL
16 April 2015, InfoQ.com

Spark SQL Explained with Examples
22 February 2023, sparkbyexamples.com

What is Spark SQL?
6 August 2022, Databricks

Spark SQL Tutorial - Learn Spark SQL
9 May 2023, intellipaat.com

Spark SQL “case when” and “when otherwise”
7 February 2023, sparkbyexamples.com

provided by Google News

VelocityDB
22 May 2018, dbdb.io

provided by Google News

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