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DBMS > Datomic vs. DolphinDB vs. Microsoft Azure Data Explorer vs. ObjectBox

System Properties Comparison Datomic vs. DolphinDB vs. Microsoft Azure Data Explorer vs. ObjectBox

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDolphinDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDolphinDB 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.Fully managed big data interactive analytics platformExtremely fast embedded database for small devices, IoT and Mobile
Primary database modelRelational DBMSTime Series 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
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Websitewww.datomic.comwww.dolphindb.comazure.microsoft.com/­services/­data-explorerobjectbox.io
Technical documentationdocs.datomic.comdocs.dolphindb.cn/­en/­help200/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.io
DeveloperCognitectDolphinDB, IncMicrosoftObjectBox Limited
Initial release2012201820192017
Current release1.0.6735, June 2023v2.00.4, January 2022cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infofree community version availablecommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++C and C++
Server operating systemsAll OS with a Java VMLinux
Windows
hostedAndroid
iOS
Linux
macOS
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
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-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.nonoyesno
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP APIJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native API
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.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 proceduresyes infoTransaction FunctionsyesYes, possible languages: KQL, Python, Rno
TriggersBy using transaction functionsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioningSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesyes 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 methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesnono
User concepts infoAccess controlnoAdministrators, Users, GroupsAzure Active Directory Authenticationyes
More information provided by the system vendor
DatomicDolphinDBMicrosoft Azure Data ExplorerObjectBox
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