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DBMS > FeatureBase vs. FileMaker vs. Microsoft Azure Data Explorer vs. MonetDB vs. PostgreSQL

System Properties Comparison FeatureBase vs. FileMaker vs. Microsoft Azure Data Explorer vs. MonetDB vs. PostgreSQL

Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonFileMaker  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMonetDB  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.FileMaker is a cross-platform RDBMS that includes a GUI frontend.Fully managed big data interactive analytics platformA relational database management system that stores data in columnsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational 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
Spatial DBMS
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
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Websitewww.featurebase.comwww.claris.com/­filemakerazure.microsoft.com/­services/­data-explorerwww.monetdb.orgwww.postgresql.org
Technical documentationdocs.featurebase.comwww.claris.com/­resources/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.monetdb.org/­Documentationwww.postgresql.org/­docs
DeveloperMolecula and Pilosa Open Source ContributorsClaris infoa subsidiary of AppleMicrosoftMonetDB BVPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20171983201920041989 info1989: Postgres, 1996: PostgreSQL
Current release2022, May 202219.4.1, November 2021cloud service with continuous releasesDec2023 (11.49), December 202316.3, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoMozilla Public License 2.0Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoCC
Server operating systemsLinux
macOS
iOS infoclient part only
Linux
OS X
Windows
hostedFreeBSD
Linux
OS X
Solaris
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesyesFixed 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-typesyesyes
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.noyes infoA http query request can return the data in XML formatyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesnoyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL queriesyes infovia pluginsKusto Query Language (KQL), SQL subsetyes infoSQL 2003 with some extensionsyes infostandard with numerous extensions
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
Filemaker WebDirect
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesJava
Python
PHP.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Ryes, in SQL, C, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding via remote tablespartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication, warm standby infosince Version 14yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none infoSource-replica replication available in experimental statusSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlsimple rights management via user accounts and connection to external directory servicesAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

More information provided by the system vendor

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