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DBMS > Kinetica vs. Machbase Neo vs. Microsoft Azure Data Explorer

System Properties Comparison Kinetica vs. Machbase Neo vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsTimeSeries DBMS for AIoT and BigDataFully managed big data interactive analytics platform
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.kinetica.commachbase.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.kinetica.commachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperKineticaMachbaseMicrosoft
Initial release201220132019
Current release7.1, August 2021V8.0, August 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercial infofree test version availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C
Server operating systemsLinuxLinux
macOS
Windows
hosted
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)
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-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.nonoyes
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoYes, possible languages: KQL, Python, R
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes infovolatile and lookup tableno
User concepts infoAccess controlAccess rights for users and roles on table levelsimple password-based access controlAzure Active Directory Authentication

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More resources
KineticaMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data Explorer
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