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DBMS > DolphinDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Vitess vs. Warp 10

System Properties Comparison DolphinDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Vitess vs. Warp 10

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVitess  Xexclude from comparisonWarp 10  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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformScalable, distributed, cloud-native DBMS, extending MySQLTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Relational DBMS infocolumn orientedRelational DBMSTime Series 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.dolphindb.comwww.graphengine.ioazure.microsoft.com/­services/­data-explorervitess.iowww.warp10.io
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorervitess.io/­docswww.warp10.io/­content/­02_Getting_started
DeveloperDolphinDB, IncMicrosoftMicrosoftThe Linux Foundation, PlanetScaleSenX
Initial release20182010201920132015
Current releasev2.00.4, January 2022cloud service with continuous releases15.0.2, December 2022
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2.0, commercial licenses availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++.NET and CGoJava
Server operating systemsLinux
Windows
.NEThostedDocker
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesschema-free
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.nonoyesno
Secondary indexesyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like query languagenoKusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsno
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, Ryes infoproprietary syntaxyes infoWarpScript
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioningSharding infoImplicit feature of the cloud serviceShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACID at shard levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes
User concepts infoAccess controlAdministrators, Users, GroupsAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or rolesMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
DolphinDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerVitessWarp 10
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