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DBMS > HEAVY.AI vs. Pinecone vs. Tigris

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

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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 comparisonTigris  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 databaseA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSVector DBMSDocument store
Key-value store
Search engine
Time Series 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
#2  Vector DBMS
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.pinecone.iowww.tigrisdata.com
Technical documentationdocs.heavy.aidocs.pinecone.io/­docs/­overviewwww.tigrisdata.com/­docs
DeveloperHEAVY.AI, Inc.Pinecone Systems, IncTigris Data, Inc.
Initial release201620192022
Current release5.10, January 2022
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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDA
Server operating systemsLinuxhostedLinux
macOS
Windows
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 SQLyesnono
APIs and other access methodsJDBC
ODBC
Thrift
Vega
RESTful HTTP APICLI Client
gRPC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
PythonGo
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles

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

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