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DBMS > Drizzle vs. Microsoft Azure AI Search vs. Spark SQL vs. Valentina Server

System Properties Comparison Drizzle vs. Microsoft Azure AI Search vs. Spark SQL vs. Valentina Server

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSpark SQL  Xexclude from comparisonValentina Server  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Search-as-a-service for web and mobile app developmentSpark SQL is a component on top of 'Spark Core' for structured data processingObject-relational database and reports server
Primary database modelRelational DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.59
Rank#63  Overall
#7  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchspark.apache.org/­sqlwww.valentina-db.net
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperDrizzle project, originally started by Brian AkerMicrosoftApache Software FoundationParadigma Software
Initial release2008201520141999
Current release7.2.4, September 2012V13.5.0 ( 2.13), September 20235.7.5
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Scala
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCRESTful HTTP APIJDBC
ODBC
ODBC
Supported programming languagesC
C++
Java
PHP
C#
Java
JavaScript
Python
Java
Python
R
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnononoyes
Triggersno infohooks for callbacks inside the server can be used.nonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPyes infousing Azure authenticationnofine grained access rights according to SQL-standard

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More resources
DrizzleMicrosoft Azure AI SearchSpark SQLValentina Server
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