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DBMS > DolphinDB vs. Faircom DB vs. FileMaker vs. Microsoft Azure Data Explorer vs. ObjectBox

System Properties Comparison DolphinDB vs. Faircom DB vs. FileMaker vs. Microsoft Azure Data Explorer vs. ObjectBox

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonFileMaker  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.FileMaker is a cross-platform RDBMS that includes a GUI frontend.Fully managed big data interactive analytics platformExtremely fast embedded database for small devices, IoT and Mobile
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedObject oriented DBMS
Secondary database modelsRelational DBMSDocument 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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Websitewww.dolphindb.comwww.faircom.com/­products/­faircom-dbwww.claris.com/­filemakerazure.microsoft.com/­services/­data-explorerobjectbox.io
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.claris.com/­resources/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.io
DeveloperDolphinDB, IncFairCom CorporationClaris infoa subsidiary of AppleMicrosoftObjectBox Limited
Initial release20181979198320192017
Current releasev2.00.4, January 2022V12, November 202019.4.1, November 2021cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree community version availablecommercial infoRestricted, free version availablecommercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ANSI C, C++C and C++
Server operating systemsLinux
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
iOS infoclient part only
Linux
OS X
Windows
hostedAndroid
iOS
Linux
macOS
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,yesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nonoyes infoA http query request can return the data in XML formatyesno
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyes, ANSI SQL with proprietary extensionsyes infovia pluginsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Filemaker WebDirect
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
PHP.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++yesYes, possible languages: KQL, Python, Rno
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnoneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replication, warm standby infosince Version 14yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayestunable from ACID to Eventually ConsistentnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlAdministrators, Users, GroupsFine grained access rights according to SQL-standard with additional protections for filessimple rights management via user accounts and connection to external directory servicesAzure Active Directory Authenticationyes
More information provided by the system vendor
DolphinDBFaircom DB infoformerly c-treeACEFileMakerMicrosoft Azure Data ExplorerObjectBox
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