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DBMS > HEAVY.AI vs. Microsoft Azure Table Storage vs. TigerGraph vs. Weaviate

System Properties Comparison HEAVY.AI vs. Microsoft Azure Table Storage vs. TigerGraph 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 comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTigerGraph  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA Wide Column Store for rapid development using massive semi-structured datasetsA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSWide column storeGraph DBMSVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Score1.83
Rank#141  Overall
#13  Graph DBMS
Score1.89
Rank#138  Overall
#4  Vector DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­en-us/­services/­storage/­tableswww.tigergraph.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.heavy.aidocs.tigergraph.comweaviate.io/­developers/­weaviate
DeveloperHEAVY.AI, Inc.MicrosoftWeaviate B.V.
Initial release2016201220172019
Current release5.10, January 20221.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialOpen 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 CUDAC++Go
Server operating systemsLinuxhostedLinux
Data schemeyesschema-freeyesyes, 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 indexesnonoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesnoSQL-like query language (GSQL)GraphQL is used as query language
APIs and other access methodsJDBC
ODBC
Thrift
Vega
RESTful HTTP APIGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnonoyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACIDno
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.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesRole-based access controlAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Table StorageTigerGraphWeaviate
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 2022Microsoft Azure Table StorageTigerGraphWeaviate
DB-Engines blog posts

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

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