DBMS > Spark SQL vs. Transwarp KunDB

System Properties Comparison Spark SQL vs. Transwarp KunDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Relational DBMS

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

Score	20.07
Rank	#35	Overall
	#21	Relational DBMS

Score	0.17
Rank	#376	Overall
	#157	Relational DBMS

Website

spark.apache.org/sql

www.transwarp.cn/en/product/kundb

Technical documentation

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

Developer

Apache Software Foundation

Transwarp

Initial release

2014

Current release

3.4.0 ( 2.13), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

Server operating systems

Linux
OS X
Windows

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

yes

APIs and other access methods

JDBC
ODBC

Supported programming languages

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

horizontal partitioning

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

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

yes

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

[Solved] . Task 4 (5 marks) Data processing with Spark Consider the... | CliffsNotes
5 June 2023, cliffsnotes.com

What is Spark SQL?
6 August 2022, Databricks

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2023
22 May 2023, Simplilearn

provided by Google News

Job opportunities

Spark SQL Developer/Engineer
eCom Solutions Inc, Remote

Spark (Databricks) Engineer – All Levels (REMOTE)
GEICO, Chevy Chase, MD

Data Scientist I/II
ABBVIE, Illinois

Jr data engineer
Kalani Consulting, Remote

Entry Level to Senior Level Software Developers
Lorven Group, Pineville, NC

jobs by

Share this page