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DBMS > FileMaker vs. Google Cloud Bigtable vs. GridDB vs. MonetDB

System Properties Comparison FileMaker vs. Google Cloud Bigtable vs. GridDB vs. MonetDB

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Editorial information provided by DB-Engines
NameFileMaker  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonMonetDB  Xexclude from comparison
DescriptionFileMaker is a cross-platform RDBMS that includes a GUI frontend.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataA relational database management system that stores data in columns
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Websitewww.claris.com/­filemakercloud.google.com/­bigtablegriddb.netwww.monetdb.org
Technical documentationwww.claris.com/­resources/­documentationcloud.google.com/­bigtable/­docsdocs.griddb.netwww.monetdb.org/­Documentation
DeveloperClaris infoa subsidiary of AppleGoogleToshiba CorporationMonetDB BV
Initial release1983201520132004
Current release19.4.1, November 20215.1, August 2022Dec2023 (11.49), December 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoMozilla Public License 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
Server operating systemsiOS infoclient part only
Linux
OS X
Windows
hostedLinuxFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes infonumerical, string, blob, geometry, boolean, timestampyes
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 formatnono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infovia pluginsnoSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL 2003 with some extensions
APIs and other access methodsFilemaker WebDirect
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesPHPC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresyesnonoyes, in SQL, C, R
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication, warm standby infosince Version 14Internal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector 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 (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID at container levelACID
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.noyes
User concepts infoAccess controlsimple rights management via user accounts and connection to external directory servicesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
FileMakerGoogle Cloud BigtableGridDBMonetDB
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
FileMakerGoogle Cloud BigtableGridDBMonetDB
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