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DBMS > Apache Spark (SQL) vs. Microsoft Azure SQL Database vs. ReductStore

System Properties Comparison Apache Spark (SQL) vs. Microsoft Azure SQL Database vs. ReductStore

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonReductStore  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingDatabase as a Service offering with high compatibility to Microsoft SQL ServerDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.40
Rank#29  Overall
#18  Relational DBMS
Score75.37
Rank#16  Overall
#11  Relational DBMS
Score0.05
Rank#357  Overall
#37  Time Series DBMS
Websitespark.apache.org/­sqlazure.microsoft.com/­en-us/­products/­azure-sql/­databasegithub.com/­reductstore
www.reduct.store
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.microsoft.com/­en-us/­azure/­azure-sqlwww.reduct.store/­docs
DeveloperApache Software FoundationMicrosoftReductStore LLC
Initial release201420102023
Current release3.5.0 ( 2.13), September 2023V121.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++C++, Rust
Server operating systemsLinux
OS X
Windows
hostedDocker
Linux
macOS
Windows
Data schemeyesyes
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 indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
HTTP API
Supported programming languagesJava
Python
R
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnoTransact SQL
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, with always 3 replicas available
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.no
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
Apache Spark (SQL)Microsoft Azure SQL Database infoformerly SQL AzureReductStore
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