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DBMS > HEAVY.AI vs. Lovefield vs. SiteWhere

System Properties Comparison HEAVY.AI vs. Lovefield vs. SiteWhere

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEmbeddable relational database for web apps written in pure JavaScriptM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.40
Rank#153  Overall
#71  Relational DBMS
Score0.22
Rank#302  Overall
#137  Relational DBMS
Score0.07
Rank#345  Overall
#31  Time Series DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldgithub.com/­sitewhere/­sitewhere
Technical documentationdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsitewhere1.sitewhere.io/­index.html
DeveloperHEAVY.AI, Inc.GoogleSiteWhere
Initial release201620142010
Current release5.10, January 20222.1.12, February 2017
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAJavaScriptJava
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Windows
Data schemeyesyespredefined scheme
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesnoyesno
SQL infoSupport of SQLyesSQL-like query language infovia JavaScript builder patternno
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HTTP REST
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
JavaScript
Server-side scripts infoStored proceduresnono
TriggersnoUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinnoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDBno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoUsers with fine-grained authorization concept

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldSiteWhere
Recent citations in the news

5 Q’s for Mike Flaxman, Vice President of Heavy.AI
15 August 2024, Center for Data Innovation

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HEAVY.AI Accelerates Big Data Analytics with Vultr’s High-Performance GPU Cloud Infrastructure
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HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

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