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DBMS > FatDB vs. IBM Db2 warehouse vs. Sequoiadb vs. Spark SQL

System Properties Comparison FatDB vs. IBM Db2 warehouse vs. Sequoiadb vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonSequoiadb  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.Cloud-based data warehousing serviceNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.34
Rank#166  Overall
#76  Relational DBMS
Score0.48
Rank#260  Overall
#41  Document stores
#121  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.ibm.com/­products/­db2/­warehousewww.sequoiadb.comspark.apache.org/­sql
Technical documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudIBMSequoiadb Ltd.Apache Software Foundation
Initial release2012201420132014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
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#C++Scala
Server operating systemsWindowshostedLinuxLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infooid, date, timestamp, binary, regexyes
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 infoImport/export of XML data possiblenono
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like query languageSQL-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
OLE DB
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesC#Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsPL/SQL, SQL PLJavaScriptno
Triggersyes infovia applicationsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardsimple password-based access controlno

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More resources
FatDBIBM Db2 warehouse infoformerly named IBM dashDBSequoiadbSpark SQL
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