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DBMS > HEAVY.AI vs. Pinecone vs. StarRocks

System Properties Comparison HEAVY.AI vs. Pinecone vs. StarRocks

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonPinecone  Xexclude from comparisonStarRocks  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA managed, cloud-native vector databaseAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelRelational DBMSVector DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score0.93
Rank#198  Overall
#93  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.pinecone.iowww.starrocks.io
Technical documentationdocs.heavy.aidocs.pinecone.io/­docs/­overviewdocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperHEAVY.AI, Inc.Pinecone Systems, IncThe Linux Foundation infosince Feb 2023
Initial release201620192020
Current release5.10, January 20223.3, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC++, Java
Server operating systemsLinuxhostedLinux
Data schemeyesyes
Typing infopredefined data types such as float or dateyesString, 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.nonono
Secondary indexesnoyes
SQL infoSupport of SQLyesnoyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
RESTful HTTP APIJDBC
MySQL protocol
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
PythonJava
Server-side scripts infoStored proceduresnouser defined functions
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinhorizontal partitioning (by range and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
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 integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardRole based access control and fine grained access rights

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

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2 June 2023, Matthias Gelbmann

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