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

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSpark SQL  Xexclude from comparisonXTDB infoformerly named Crux  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.Search-as-a-service for web and mobile app developmentSpark SQL is a component on top of 'Spark Core' for structured data processingA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelDocument store
Key-value store
Search engineRelational DBMSDocument store
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.71
Rank#64  Overall
#8  Search engines
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.09
Rank#351  Overall
#47  Document stores
Websiteazure.microsoft.com/­en-us/­services/­searchspark.apache.org/­sqlgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.xtdb.com/­docs
DeveloperFatCloudMicrosoftApache Software FoundationJuxt Ltd.
Initial release2012201520142019
Current releaseV13.5.0 ( 2.13), September 20231.19, September 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoMIT License
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#ScalaClojure
Server operating systemsWindowshostedLinux
OS X
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation format
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementslimited SQL, making use of Apache Calcite
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIJDBC
ODBC
HTTP REST
JDBC
Supported programming languagesC#C#
Java
JavaScript
Python
Java
Python
R
Scala
Clojure
Java
Server-side scripts infoStored proceduresyes infovia applicationsnonono
Triggersyes infovia applicationsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud servicenoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsyes infousing Azure authenticationno

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More resources
FatDBMicrosoft Azure AI SearchSpark SQLXTDB infoformerly named Crux
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