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DBMS > Heroic vs. ObjectBox vs. Sphinx vs. Weaviate

System Properties Comparison Heroic vs. ObjectBox vs. Sphinx vs. Weaviate

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchExtremely fast embedded database for small devices, IoT and MobileOpen source search engine for searching in data from different sources, e.g. relational databasesAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelTime Series DBMSObject oriented DBMSSearch engineVector DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitegithub.com/­spotify/­heroicobjectbox.iosphinxsearch.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationspotify.github.io/­heroicdocs.objectbox.iosphinxsearch.com/­docsweaviate.io/­developers/­weaviate
DeveloperSpotifyObjectBox LimitedSphinx Technologies Inc.Weaviate B.V.
Initial release2014201720012019
Current release3.5.1, February 20231.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache License 2.0Open Source infoGPL version 2, commercial licence availableOpen 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 languageJavaC and C++C++Go
Server operating systemsAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesnoyes 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 indexesyes infovia Elasticsearchyesyes infofull-text index on all search fieldsyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnonoSQL-like query language (SphinxQL)GraphQL is used as query language
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
Proprietary native APIProprietary protocolGraphQL query language
RESTful HTTP/JSON API
Supported programming languagesC
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesonline/offline synchronization between client and servernoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlyesnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
HeroicObjectBoxSphinxWeaviate
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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