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DBMS > HEAVY.AI vs. Kinetica vs. Realm vs. Vertica

System Properties Comparison HEAVY.AI vs. Kinetica vs. Realm vs. Vertica

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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 comparisonRealm  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comrealm.iowww.vertica.com
Technical documentationdocs.heavy.aidocs.kinetica.comrealm.io/­docsvertica.com/­documentation
DeveloperHEAVY.AI, Inc.KineticaRealm, acquired by MongoDB in May 2019OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2016201220142005
Current release5.10, January 20227.1, August 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC, C++C++
Server operating systemsLinuxLinuxAndroid
Backend: server-less
iOS
Windows
Linux
Data schemeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesnoyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functionsno inforuns within the applications so server-side scripts are unnecessaryyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoChange Listenersyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 infoIn-Memory realmno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaRealmVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaRealmVertica infoOpenText™ Vertica™
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