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

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

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDolphinDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityDolphinDB 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 platformTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSTime Series DBMSGraph DBMS
Key-value store
Relational DBMS infocolumn orientedTime 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
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
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.dolphindb.comwww.graphengine.ioazure.microsoft.com/­services/­data-explorerwww.warp10.io
Technical documentationdocs.databend.comdocs.dolphindb.cn/­en/­help200/­index.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerwww.warp10.io/­content/­02_Getting_started
DeveloperDatabend LabsDolphinDB, IncMicrosoftMicrosoftSenX
Initial release20212018201020192015
Current release1.0.59, April 2023v2.00.4, January 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community version availableOpen Source infoMIT LicensecommercialOpen 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 languageRustC++.NET and CJava
Server operating systemshosted
Linux
macOS
Linux
Windows
.NEThostedLinux
OS X
Windows
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)schema-free
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-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.nononoyesno
Secondary indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLyesSQL-like query languagenoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
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
HTTP API
Jupyter
WebSocket
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyesyesYes, possible languages: KQL, Python, Ryes infoWarpScript
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioninghorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
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 infobased on HBase
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAdministrators, Users, GroupsAzure Active Directory AuthenticationMandatory use of cryptographic tokens, containing fine-grained authorizations

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DatabendDolphinDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerWarp 10
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