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DBMS > Apache Spark (SQL) vs. Databricks

System Properties Comparison Apache Spark (SQL) vs. Databricks

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonDatabricks  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.
Primary database modelRelational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.45
Rank#31  Overall
#19  Relational DBMS
Score90.03
Rank#13  Overall
#2  Document stores
#9  Relational DBMS
Websitespark.apache.org/­sqlwww.databricks.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.databricks.com
DeveloperApache Software FoundationDatabricks
Initial release20142013
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux
OS X
Windows
hosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyes
Secondary indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQL
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Supported programming languagesJava
Python
R
Scala
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions and aggregates
Triggersno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlno
More information provided by the system vendor
Apache Spark (SQL)Databricks
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache Spark (SQL)Databricks
DB-Engines blog posts

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Recent citations in the news

How to run Pandas code on Spark
25 January 2025, data-ai.theodo.com

Introducing generative AI troubleshooting for Apache Spark in AWS Glue (preview)
22 November 2024, AWS Blog

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22 January 2025, TechTarget

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2025
12 November 2024, Simplilearn

Query Execution Optimization in Spark SQL - Ji - 2020 - Scientific Programming
13 June 2024, Wiley Online Library

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