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DBMS > DolphinDB vs. FileMaker vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. OrigoDB

System Properties Comparison DolphinDB vs. FileMaker vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. OrigoDB

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonFileMaker  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  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.FileMaker is a cross-platform RDBMS that includes a GUI frontend.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFully managed big data interactive analytics platformA fully ACID in-memory object graph database
Primary database modelTime Series DBMSRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infocolumn orientedDocument store
Object oriented DBMS
Secondary database modelsRelational DBMSGraph DBMS
Search engine
Document 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websitewww.dolphindb.comwww.claris.com/­filemakerwww.gigaspaces.comazure.microsoft.com/­services/­data-explorerorigodb.com
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlwww.claris.com/­resources/­documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docs
DeveloperDolphinDB, IncClaris infoa subsidiary of AppleGigaspaces TechnologiesMicrosoftRobert Friberg et al
Initial release20181983200020192009 infounder the name LiveDB
Current releasev2.00.4, January 202219.4.1, November 202115.5, September 2020cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree community version availablecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source
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++Java, C++, .NetC#
Server operating systemsLinux
Windows
iOS infoclient part only
Linux
OS X
Windows
Linux
macOS
Solaris
Windows
hostedLinux
Windows
Data schemeyesyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes 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 collections
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 formatno infoXML can be used for describing objects metadatayesno infocan be achieved using .NET
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyes infovia pluginsSQL-99 for query and DML statementsKusto 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
Filemaker WebDirect
JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
PHP.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Server-side scripts infoStored proceduresyesyesyesYes, possible languages: KQL, Python, Ryes
Triggersnoyesyes, event driven architectureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication, warm standby infosince Version 14Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoMap-Reduce pattern can be built with XAP task executorsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAdministrators, Users, Groupssimple rights management via user accounts and connection to external directory servicesRole-based access controlAzure Active Directory AuthenticationRole based authorization

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More resources
DolphinDBFileMakerGigaSpacesMicrosoft Azure Data ExplorerOrigoDB
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