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DBMS > HEAVY.AI vs. Kinetica vs. Milvus vs. Tkrzw

System Properties Comparison HEAVY.AI vs. Kinetica vs. Milvus vs. Tkrzw

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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 comparisonMilvus  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 DBMS designed for efficient storage of vector data and vector similarity searchesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSRelational DBMSVector DBMSKey-value store
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series 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
Score3.01
Rank#89  Overall
#4  Vector DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.commilvus.iodbmx.net/­tkrzw
Technical documentationdocs.heavy.aidocs.kinetica.commilvus.io/­docs/­overview.md
DeveloperHEAVY.AI, Inc.KineticaMikio Hirabayashi
Initial release2016201220192020
Current release5.10, January 20227.1, August 20212.4.4, May 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++ and CUDAC, C++C++, GoC++
Server operating systemsLinuxLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringno
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 indexesnoyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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 RAMyesyes infousing specific database classes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelRole based access control and fine grained access rightsno
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaMilvusTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaMilvusTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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