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DBMS > FileMaker vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. OrigoDB vs. PostgreSQL

System Properties Comparison FileMaker vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. OrigoDB vs. PostgreSQL

Editorial information provided by DB-Engines
NameFileMaker  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionFileMaker is a cross-platform RDBMS that includes a GUI frontend.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Fully managed big data interactive analytics platformA fully ACID in-memory object graph databaseWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSDocument storeRelational DBMS infocolumn orientedDocument store
Object oriented DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitewww.claris.com/­filemakerfirebase.google.com/­products/­firestoreazure.microsoft.com/­services/­data-explorerorigodb.comwww.postgresql.org
Technical documentationwww.claris.com/­resources/­documentationfirebase.google.com/­docs/­firestoredocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docswww.postgresql.org/­docs
DeveloperClaris infoa subsidiary of AppleGoogleMicrosoftRobert Friberg et alPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release1983201720192009 infounder the name LiveDB1989 info1989: Postgres, 1996: PostgreSQL
Current release19.4.1, November 2021cloud service with continuous releases16.3, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen SourceOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C
Server operating systemsiOS infoclient part only
Linux
OS X
Windows
hostedhostedLinux
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesUser defined using .NET types and collectionsyes
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 formatnoyesno infocan be achieved using .NETyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyes infovia pluginsnoKusto Query Language (KQL), SQL subsetnoyes infostandard with numerous extensions
APIs and other access methodsFilemaker WebDirect
JDBC
ODBC
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPHPGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesyes, Firebase Rules & Cloud FunctionsYes, possible languages: KQL, Python, Ryesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyesyes, with Cloud Functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication, warm standby infosince Version 14Multi-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonodepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
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. Security Rules for 3rd party authentication using Firebase Auth.Azure Active Directory AuthenticationRole based authorizationfine grained access rights according to SQL-standard

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FileMakerGoogle Cloud FirestoreMicrosoft Azure Data ExplorerOrigoDBPostgreSQL
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