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DBMS > Badger vs. Heroic vs. Weaviate

System Properties Comparison Badger vs. Heroic vs. Weaviate

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHeroic  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA cloud-native, realtime vector search engine integrating scalable machine learning models
Primary database modelKey-value storeTime Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#302  Overall
#44  Key-value stores
Score0.07
Rank#315  Overall
#29  Time Series DBMS
Score0.18
Rank#292  Overall
#15  Search engines
Websitegithub.com/­dgraph-io/­badgerspotify.github.io/­heroic/­#!/­indexgithub.com/­semi-technologies/­weaviate
www.semi.technology/­solutions/­weaviate
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerspotify.github.io/­heroic/­#!/­docs/­overviewwww.semi.technology/­developers/­weaviate/­current
DeveloperDGraph LabsSpotifySeMI Technologies B.V.
Initial release201720142017
Current release1.0.3, January 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaGo
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or datenoyesyes 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.nonono
Secondary indexesnoyes infovia Elasticsearchyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnonoGraphQL is used as query language
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesGo
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnoOpenID Connect Discovery
More information provided by the system vendor
BadgerHeroicWeaviate
News

Weaviate in IEEE

Weaviate on DB-engines.com

Introduction & Demo video

FLOSS Weekly Podcast

FOSDEM 2020 video

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More resources
BadgerHeroicWeaviate
DB-Engines blog posts

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

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