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DBMS > Badger vs. HEAVY.AI vs. Lovefield vs. Weaviate

System Properties Comparison Badger vs. HEAVY.AI vs. Lovefield vs. Weaviate

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEmbeddable relational database for web apps written in pure JavaScriptAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelKey-value storeRelational DBMSRelational DBMSVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#328  Overall
#48  Key-value stores
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score0.22
Rank#306  Overall
#138  Relational DBMS
Score1.48
Rank#149  Overall
#8  Vector DBMS
Websitegithub.com/­dgraph-io/­badgergithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdweaviate.io/­developers/­weaviate
DeveloperDGraph LabsHEAVY.AI, Inc.GoogleWeaviate B.V.
Initial release2017201620142019
Current release5.10, January 20222.1.12, February 20171.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infocommercial license available with Weaviate Enterprise
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.
Implementation languageGoC++ and CUDAJavaScriptGo
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemeschema-freeyesyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or datenoyesyesyes 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 indexesnonoyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnoyesSQL-like query language infovia JavaScript builder patternGraphQL is used as query language
APIs and other access methodsJDBC
ODBC
Thrift
Vega
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesGoAll languages supporting JDBC/ODBC/Thrift
Python
JavaScriptJavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnononono
TriggersnonoUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoRound robinnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDByes
User concepts infoAccess controlnofine grained access rights according to SQL-standardnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
BadgerHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldWeaviate
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...
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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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BadgerHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldWeaviate
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