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DBMS > HEAVY.AI vs. Kinetica vs. Microsoft Azure Data Explorer vs. UniData,UniVerse

System Properties Comparison HEAVY.AI vs. Kinetica vs. Microsoft Azure Data Explorer vs. UniData,UniVerse

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedMultivalue DBMS
Secondary database modelsSpatial DBMSSpatial 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
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score3.47
Rank#93  Overall
#2  Multivalue DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comazure.microsoft.com/­services/­data-explorerwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationdocs.heavy.aidocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperHEAVY.AI, Inc.KineticaMicrosoftRocket Software
Initial release2016201220191985
Current release5.10, January 20227.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC, C++C
Server operating systemsLinuxLinuxhostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-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-typesoptional
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 indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, Ryes
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infoconfigurable
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.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelAzure Active Directory AuthenticationAccess rights according to SQL-standard and operating system based

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaMicrosoft Azure Data ExplorerUniData,UniVerse
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