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DBMS > HEAVY.AI vs. Kinetica vs. Pinecone vs. TigerGraph

System Properties Comparison HEAVY.AI vs. Kinetica vs. Pinecone vs. TigerGraph

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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 comparisonPinecone  Xexclude from comparisonTigerGraph  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 managed, cloud-native vector databaseA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSRelational DBMSVector DBMSGraph DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comwww.pinecone.iowww.tigergraph.com
Technical documentationdocs.heavy.aidocs.kinetica.comdocs.pinecone.io/­docs/­overviewdocs.tigergraph.com
DeveloperHEAVY.AI, Inc.KineticaPinecone Systems, Inc
Initial release2016201220192017
Current release5.10, January 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC, C++C++
Server operating systemsLinuxLinuxhostedLinux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesString, Number, Booleanyes
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 indexesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoSQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
PythonC++
Java
Server-side scripts infoStored proceduresnouser defined functionsyes
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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 RAMnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelRole-based access control

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaPineconeTigerGraph
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

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