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DBMS > HEAVY.AI vs. Kinetica vs. MongoDB

System Properties Comparison HEAVY.AI vs. Kinetica vs. MongoDB

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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 comparisonMongoDB  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 CPUsOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSRelational DBMSDocument store
Secondary database modelsSpatial DBMSSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.48
Rank#146  Overall
#70  Relational DBMS
Score0.55
Rank#230  Overall
#110  Relational DBMS
Score477.66
Rank#5  Overall
#1  Document stores
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comwww.mongodb.com
Technical documentationdocs.heavy.aiwww.kinetica.com/­docsdocs.mongodb.com/­manual
DeveloperHEAVY.AI, Inc.KineticaMongoDB, Inc
Initial release201620122009
Current release5.10, January 20227.1, August 20216.0.0, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.
Cloud-based only infoOnly available as a cloud servicenonono infoMongoDB available as DBaaS (MongoDB Atlas)
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC, C++C++
Server operating systemsLinuxLinuxLinux
OS X
Solaris
Windows
Data schemeyesyesschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatial
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.nono
Secondary indexesnoyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
proprietary protocol using JSON
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
Server-side scripts infoStored proceduresnouser defined functionsJavaScript
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynoyesno infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by default
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 storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelAccess rights for users and roles
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaMongoDB
Specific characteristicsOptimizes memory and compute layers to deliver unprecedented performance. Natively...
» more
Native and fully vectorized database across both GPUs and CPUs, with memory first...
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MongoDB’s application data platform provides developers a unified interface to power...
» more
Competitive advantagesOnly HEAVY.AI allows users to visually and interactively discover high-value patterns,...
» more
Best in class geospatial and temporal analytics. Lockless architecture provides real-time...
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The MongoDB platform can be used by developers building transactional, operational,...
» more
Typical application scenariosAdvanced analytics, geospatial and time-series analytics, accelerated data science,...
» more
Any application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Internet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
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Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
200+ million downloads, over 1.5M Atlas database clusters under management handling...
» more
Licensing and pricing modelsHEAVY.AI Free (Free Forever), Foundations ($2k/month), and Enterprise Licensure (Inquire...
» more
Always Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more
MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaMongoDB
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The insideBIGDATA IMPACT 50 List for Q3 2022
19 July 2022, insideBIGDATA

OmniSci Gets HEAVY New Name and New CEO
1 March 2022, Datanami

HEAVY.AI Introduces New Capabilities that Enable Organizations to Gain Faster Access to Rapidly Growing Data Sets and Deliver Decision-Quality Information
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3 August 2022, Benzinga

Kinetica Now Accessible as a Service on Microsoft Azure
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