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DBMS > HEAVY.AI vs. HyperSQL vs. jBASE vs. Kinetica vs. Microsoft Azure Data Explorer

System Properties Comparison HEAVY.AI vs. HyperSQL vs. jBASE vs. Kinetica vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMSMultivalue DBMSRelational DBMSRelational DBMS infocolumn oriented
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
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
hsqldb.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.heavy.aihsqldb.org/­web/­hsqlDocsFrame.htmldocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHEAVY.AI, Inc.Rocket Software (formerly Zumasys)KineticaMicrosoft
Initial release20162001199120122019
Current release5.10, January 20222.7.2, June 20235.77.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infobased on BSD licensecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAJavaC, C++
Server operating systemsLinuxAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesAIX
Linux
Windows
Linuxhosted
Data schemeyesyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesoptionalyesyes 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.nonoyesnoyes
Secondary indexesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLyesyesEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HTTP API infoJDBC via HTTP
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
All languages supporting JDBC/ODBC
Java
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoJava, SQLyesuser defined functionsYes, possible languages: KQL, Python, R
Triggersnoyesyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinnoneShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneyesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAccess rights for users and roles on table levelAzure Active Directory Authentication

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HyperSQL infoalso known as HSQLDBjBASEKineticaMicrosoft Azure Data Explorer
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