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DBMS > FatDB vs. FeatureBase vs. Spark SQL

System Properties Comparison FatDB vs. FeatureBase vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonFeatureBase  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.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.featurebase.comspark.apache.org/­sql
Technical documentationdocs.featurebase.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudMolecula and Pilosa Open Source ContributorsApache Software Foundation
Initial release201220172014
Current release2022, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#GoScala
Server operating systemsWindowsLinux
macOS
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesnono
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL queriesSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
Supported programming languagesC#Java
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsno
Triggersyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsno

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More resources
FatDBFeatureBaseSpark SQL
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