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DBMS > FileMaker vs. Google Cloud Datastore vs. Microsoft Access vs. Spark SQL

System Properties Comparison FileMaker vs. Google Cloud Datastore vs. Microsoft Access vs. Spark SQL

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Editorial information provided by DB-Engines
NameFileMaker  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFileMaker is a cross-platform RDBMS that includes a GUI frontend.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.claris.com/­filemakercloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accessspark.apache.org/­sql
Technical documentationwww.claris.com/­resources/­documentationcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accessspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperClaris infoa subsidiary of AppleGoogleMicrosoftApache Software Foundation
Initial release1983200819922014
Current release19.4.1, November 20211902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficeOpen 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++Scala
Server operating systemsiOS infoclient part only
Linux
OS X
Windows
hostedWindows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 indexesyesyesyesno
SQL infoSupport of SQLyes infovia pluginsSQL-like query language (GQL)yes infobut not compliant to any SQL standardSQL-like DML and DDL statements
APIs and other access methodsFilemaker WebDirect
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesPHP.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesusing Google App Engineyes infosince Access 2010 using the ACE-engineno
TriggersyesCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication, warm standby infosince Version 14Multi-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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)no infoa simple user-level security was built in till version Access 2003no

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More resources
FileMakerGoogle Cloud DatastoreMicrosoft AccessSpark SQL
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