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DBMS > FatDB vs. Ingres vs. Microsoft Azure AI Search vs. Spark SQL

System Properties Comparison FatDB vs. Ingres vs. Microsoft Azure AI Search vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Well established RDBMSSearch-as-a-service for web and mobile app developmentSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSSearch engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.actian.com/­databases/­ingresazure.microsoft.com/­en-us/­services/­searchspark.apache.org/­sql
Technical documentationdocs.actian.com/­ingreslearn.microsoft.com/­en-us/­azure/­searchspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudActian CorporationMicrosoftApache Software Foundation
Initial release20121974 infooriginally developed at University Berkely in early 1970s20152014
Current release11.2, May 2022V13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#CScala
Server operating systemsWindowsAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeyesyesyes
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.no infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesnoSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC#C#
Java
JavaScript
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyesnono
Triggersyes infovia applicationsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorIngres Replicatoryes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
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.nonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardyes infousing Azure authenticationno

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More resources
FatDBIngresMicrosoft Azure AI SearchSpark SQL
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