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DBMS > DolphinDB vs. Heroic vs. Linter vs. Microsoft Azure Data Explorer

System Properties Comparison DolphinDB vs. Heroic vs. Linter vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonHeroic  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  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.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchRDBMS for high security requirementsFully managed big data interactive analytics platform
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsRelational DBMSSpatial 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.23
Rank#82  Overall
#6  Time Series DBMS
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score0.10
Rank#350  Overall
#153  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitewww.dolphindb.comgithub.com/­spotify/­heroiclinter.ruazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDolphinDB, IncSpotifyrelex.ruMicrosoft
Initial release2018201419902019
Current releasev2.00.4, January 2022cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC and C++
Server operating systemsLinux
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
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-types
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.nononoyes
Secondary indexesyesyes infovia Elasticsearchyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, R
Triggersnonoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAdministrators, Users, Groupsfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
DolphinDBHeroicLinterMicrosoft Azure Data Explorer
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