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DBMS > Apache Spark (SQL) vs. Snowflake

System Properties Comparison Apache Spark (SQL) vs. Snowflake

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Our visitors often compare Apache Spark (SQL) and Snowflake with PostgreSQL, Trino and MySQL.

Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonSnowflake  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingCloud-based data warehousing service for structured and semi-structured data
Primary database modelRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score21.62
Rank#29  Overall
#18  Relational DBMS
Score172.01
Rank#6  Overall
#5  Relational DBMS
Websitespark.apache.org/­sqlwww.snowflake.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.snowflake.net/­manuals/­index.html
DeveloperApache Software FoundationSnowflake Computing Inc.
Initial release20142014
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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScala
Server operating systemsLinux
OS X
Windows
hosted
Data schemeyesyes infosupport of semi-structured data formats (JSON, XML, Avro)
Typing infopredefined data types such as float or dateyesyes
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 indexesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
CLI Client
JDBC
ODBC
Supported programming languagesJava
Python
R
Scala
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions
Triggersnono infosimilar concept for controling cloud resources
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Coreyes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyes
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 controlnoUsers with fine-grained authorization concept, user roles and pluggable authentication

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More resources
Apache Spark (SQL)Snowflake
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