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DBMS > FileMaker vs. GridDB vs. Kinetica vs. Spark SQL

System Properties Comparison FileMaker vs. GridDB vs. Kinetica vs. Spark SQL

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Editorial information provided by DB-Engines
NameFileMaker  Xexclude from comparisonGridDB  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFileMaker is a cross-platform RDBMS that includes a GUI frontend.Scalable in-memory time series database optimized for IoT and Big DataFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.claris.com/­filemakergriddb.netwww.kinetica.comspark.apache.org/­sql
Technical documentationwww.claris.com/­resources/­documentationdocs.griddb.netdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperClaris infoa subsidiary of AppleToshiba CorporationKineticaApache Software Foundation
Initial release1983201320122014
Current release19.4.1, November 20215.1, August 20227.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++Scala
Server operating systemsiOS infoclient part only
Linux
OS X
Windows
LinuxLinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.yes infoA http query request can return the data in XML formatnonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infovia pluginsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsFilemaker WebDirect
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesPHPC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnouser defined functionsno
Triggersyesyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication, warm standby infosince Version 14Source-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnono
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.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlsimple rights management via user accounts and connection to external directory servicesAccess rights for users can be defined per databaseAccess rights for users and roles on table levelno
More information provided by the system vendor
FileMakerGridDBKineticaSpark SQL
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
FileMakerGridDBKineticaSpark SQL
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