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DBMS > Microsoft Azure AI Search vs. OrigoDB vs. Spark SQL vs. Tigris

System Properties Comparison Microsoft Azure AI Search vs. OrigoDB vs. Spark SQL vs. Tigris

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelSearch engineDocument store
Object oriented DBMS
Relational DBMSDocument store
Key-value store
Search engine
Time Series 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
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.02
Rank#369  Overall
#51  Document stores
#55  Key-value stores
#24  Search engines
#38  Time Series DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchorigodb.comspark.apache.org/­sqlwww.tigrisdata.com
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tigrisdata.com/­docs
DeveloperMicrosoftRobert Friberg et alApache Software FoundationTigris Data, Inc.
Initial release20152009 infounder the name LiveDB20142022
Current releaseV13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#Scala
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyesyes
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 infocan be achieved using .NETnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP API.NET Client API
HTTP API
LINQ
JDBC
ODBC
CLI Client
gRPC
RESTful HTTP API
Supported programming languagesC#
Java
JavaScript
Python
.NetJava
Python
R
Scala
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyes infoDomain Eventsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlyes infousing Azure authenticationRole based authorizationnoAccess rights for users and roles

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More resources
Microsoft Azure AI SearchOrigoDBSpark SQLTigris
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