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DBMS > Heroic vs. Weaviate vs. Yanza

System Properties Comparison Heroic vs. Weaviate vs. Yanza

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonWeaviate  Xexclude from comparisonYanza  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA cloud-native, realtime vector search engine integrating scalable machine learning modelsTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSSearch engineTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.07
Rank#315  Overall
#29  Time Series DBMS
Score0.18
Rank#292  Overall
#15  Search engines
Score0.00
Rank#353  Overall
#34  Time Series DBMS
Websitespotify.github.io/­heroic/­#!/­indexgithub.com/­semi-technologies/­weaviate
www.semi.technology/­solutions/­weaviate
yanza.com
Technical documentationspotify.github.io/­heroic/­#!/­docs/­overviewwww.semi.technology/­developers/­weaviate/­current
DeveloperSpotifySeMI Technologies B.V.Yanza
Initial release201420172015
Current release1.0.3, January 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infocommercial license available with Weaviate Enterprisecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemsWindows
Data schemeschema-freeyes, maps to GraphQL interfaceschema-free
Typing infopredefined data types such as float or dateyesyes infostring, int, float, geo point, date, cross reference, fuzzy referencesno
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 indexesyes infovia Elasticsearchyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexedno
SQL infoSupport of SQLnoGraphQL is used as query languageno
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
GraphQL query language
RESTful HTTP/JSON API
HTTP API
Supported programming languagesany language that supports HTTP calls
Server-side scripts infoStored proceduresnonono
Triggersnonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate 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.nono
User concepts infoAccess controlOpenID Connect Discoveryno
More information provided by the system vendor
HeroicWeaviateYanza
News

Weaviate in IEEE

Weaviate on DB-engines.com

Introduction & Demo video

FLOSS Weekly Podcast

FOSDEM 2020 video

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More resources
HeroicWeaviateYanza
DB-Engines blog posts

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

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Recent citations in the news

Weaviate is an open-source search engine powered by ML, vectors, graphs, and GraphQL
7 April 2021, ZDNet

Getting Started with the Weaviate Vector Search Engine
18 May 2020, hackernoon.com

The History of the Weaviate Vector Search Engine
9 May 2020, hackernoon.com

Weaviate Is A Search Engine For Vector Embeddings
11 May 2020, hackernoon.com

Why the rise of vector databases is a revolution for data analysis
7 July 2021, TechGenix

provided by Google News



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