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DBMS > HEAVY.AI vs. IBM Db2 warehouse vs. Realm vs. Weaviate

System Properties Comparison HEAVY.AI vs. IBM Db2 warehouse vs. Realm vs. Weaviate

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonRealm  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareCloud-based data warehousing serviceA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSRelational DBMSDocument storeVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.ibm.com/­products/­db2/­warehouserealm.iogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.heavy.airealm.io/­docsweaviate.io/­developers/­weaviate
DeveloperHEAVY.AI, Inc.IBMRealm, acquired by MongoDB in May 2019Weaviate B.V.
Initial release2016201420142019
Current release5.10, January 20221.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen SourceOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAGo
Server operating systemsLinuxhostedAndroid
Backend: server-less
iOS
Windows
Data schemeyesyesyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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.nono infoImport/export of XML data possiblenono
Secondary indexesnoyesyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesyesnoGraphQL is used as query language
APIs and other access methodsJDBC
ODBC
Thrift
Vega
.NET Client API
JDBC
ODBC
OLE DB
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnoPL/SQL, SQL PLno inforuns within the applications so server-side scripts are unnecessaryno
Triggersnoyesyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesyesyes infoIn-Memory realmyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyesAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM Db2 warehouse infoformerly named IBM dashDBRealmWeaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM Db2 warehouse infoformerly named IBM dashDBRealmWeaviate
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Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

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14 April 2023, InfoWorld

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16 February 2023, Datanami

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