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DBMS > Kinetica vs. Lovefield vs. Microsoft Azure Data Explorer

System Properties Comparison Kinetica vs. Lovefield vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsEmbeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational 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
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.kinetica.comgoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.kinetica.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperKineticaGoogleMicrosoft
Initial release201220142019
Current release7.1, August 20212.1.12, February 2017cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaScript
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safarihosted
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 language infovia JavaScript builder patternKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
JavaScript.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 rangeUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes 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 integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
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 infousing MemoryDBno
User concepts infoAccess controlAccess rights for users and roles on table levelnoAzure Active Directory Authentication

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More resources
KineticaLovefieldMicrosoft Azure Data Explorer
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