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DBMS > FatDB vs. Ingres vs. Kdb vs. Spark SQL

System Properties Comparison FatDB vs. Ingres vs. Kdb vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonIngres  Xexclude from comparisonKdb  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 RDBMSHigh performance Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.actian.com/­databases/­ingreskx.comspark.apache.org/­sql
Technical documentationdocs.actian.com/­ingrescode.kx.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudActian CorporationKx Systems, a division of First Derivatives plcApache Software Foundation
Initial release20121974 infooriginally developed at University Berkely in early 1970s2000 infokdb was released 2000, kdb+ in 20032014
Current release11.2, May 20223.6, May 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree 32-bit versionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#CqScala
Server operating systemsWindowsAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
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 availableyesno
Secondary indexesyesyesyes infotable attribute 'grouped'no
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like query language (q)SQL-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)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
Supported programming languagesC#C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyesuser defined functionsno
Triggersyes infovia applicationsyesyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyhorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorIngres ReplicatorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
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.noyesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardrights management via user accountsno
More information provided by the system vendor
FatDBIngresKdbSpark SQL
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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FatDBIngresKdbSpark SQL
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