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DBMS > HEAVY.AI vs. Kinetica vs. Lovefield vs. SingleStore vs. SpatiaLite

System Properties Comparison HEAVY.AI vs. Kinetica vs. Lovefield vs. SingleStore vs. SpatiaLite

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonLovefield  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonSpatiaLite  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 CPUsEmbeddable relational database for web apps written in pure JavaScriptMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeSpatial extension of SQLite
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSSpatial DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.22
Rank#306  Overall
#138  Relational DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Score1.56
Rank#142  Overall
#3  Spatial DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comgoogle.github.io/­lovefieldwww.singlestore.comwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationdocs.heavy.aidocs.kinetica.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.singlestore.comwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperHEAVY.AI, Inc.KineticaGoogleSingleStore Inc.Alessandro Furieri
Initial release20162012201420132008
Current release5.10, January 20227.1, August 20212.1.12, February 20178.5, January 20245.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache 2.0commercial infofree developer edition availableOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC, C++JavaScriptC++, GoC++
Server operating systemsLinuxLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux info64 bit version requiredserver-less
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language infovia JavaScript builder patternyes infobut no triggers and foreign keysyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
JavaScriptBash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functionsnoyesno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeUsing read-only observersnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingnoneSharding infohash partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationnoneSource-replica replication infostores two copies of each physical data partition on two separate nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infocan define user-defined aggregate functions for map-reduce-style calculationsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
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 infousing MemoryDByesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelnoFine grained access control via users, groups and rolesno

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaLovefieldSingleStore infoformer name was MemSQLSpatiaLite
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Recent citations in the news

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series
19 September 2024, Unite.AI

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