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DBMS > HEAVY.AI vs. Machbase Neo vs. Microsoft Azure AI Search vs. Weaviate

System Properties Comparison HEAVY.AI vs. Machbase Neo vs. Microsoft Azure AI Search 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 comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareTimeSeries DBMS for AIoT and BigDataSearch-as-a-service for web and mobile app developmentAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSTime Series DBMSSearch engineVector DBMS
Secondary database modelsSpatial DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
machbase.comazure.microsoft.com/­en-us/­services/­searchgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.heavy.aimachbase.com/­dbmslearn.microsoft.com/­en-us/­azure/­searchweaviate.io/­developers/­weaviate
DeveloperHEAVY.AI, Inc.MachbaseMicrosoftWeaviate B.V.
Initial release2016201320152019
Current release5.10, January 2022V8.0, August 2023V11.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercial infofree test version availablecommercialOpen Source infocommercial license available with Weaviate Enterprise
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 CUDACGo
Server operating systemsLinuxLinux
macOS
Windows
hosted
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.nononono
Secondary indexesnoyesyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesSQL-like query languagenoGraphQL is used as query language
APIs and other access methodsJDBC
ODBC
Thrift
Vega
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP APIGraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
C#
Java
JavaScript
Python
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factoryes infoImplicit feature of the cloud serviceyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infovolatile and lookup tablenoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardsimple password-based access controlyes infousing Azure authenticationAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Machbase Neo infoFormer name was InfinifluxMicrosoft Azure AI SearchWeaviate
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 2022Machbase Neo infoFormer name was InfinifluxMicrosoft Azure AI SearchWeaviate
DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021,  Etienne Dilocker, SeMI Technologies (sponsor) 

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