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DBMS > HEAVY.AI vs. Kinetica vs. Solr vs. UniData,UniVerse

System Properties Comparison HEAVY.AI vs. Kinetica vs. Solr 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 comparisonSolr  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 CPUsA widely used distributed, scalable search engine based on Apache LuceneMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelRelational DBMSRelational DBMSSearch engineMultivalue DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Spatial DBMS
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
Score44.28
Rank#24  Overall
#3  Search engines
Score3.47
Rank#93  Overall
#2  Multivalue DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comsolr.apache.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationdocs.heavy.aidocs.kinetica.comsolr.apache.org/­resources.htmldocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperHEAVY.AI, Inc.KineticaApache Software FoundationRocket Software
Initial release2016201220061985
Current release5.10, January 20227.1, August 20219.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC, C++JavaC
Server operating systemsLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingoptional
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 indexesnoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON 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
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresnouser defined functionsJava pluginsyes
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACID 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 RAMyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelyesAccess 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 2022KineticaSolrUniData,UniVerse
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Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

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14 April 2023, InfoWorld

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16 February 2023, Datanami

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26 March 2024, Datanami

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21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

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30 October 2023, InfoWorld

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Closing Bell: Solar Alliance Energy Inc flat on Friday (SOLR)
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SOLR-led walkout demands better conditions for Compass workers
27 February 2024, Daily Northwestern

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