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DBMS > Heroic vs. Solr vs. Sphinx vs. Weaviate

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

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA widely used distributed, scalable search engine based on Apache LuceneOpen 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 DBMSSearch engineSearch engineVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitegithub.com/­spotify/­heroicsolr.apache.orgsphinxsearch.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationspotify.github.io/­heroicsolr.apache.org/­resources.htmlsphinxsearch.com/­docsweaviate.io/­developers/­weaviate
DeveloperSpotifyApache Software FoundationSphinx Technologies Inc.Weaviate B.V.
Initial release2014200620012019
Current release9.6.0, April 20243.5.1, February 20231.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open 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 languageJavaJavaC++Go
Server operating systemsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingnoyes 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.noyesno
Secondary indexesyes infovia Elasticsearchyes infoAll search fields are automatically indexedyes 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 SQLnoSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)GraphQL is used as query language
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
Java API
RESTful HTTP/JSON API
Proprietary protocolGraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnoJava pluginsnono
Triggersnoyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnono
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.noyesyes
User concepts infoAccess controlyesnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
HeroicSolrSphinxWeaviate
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
HeroicSolrSphinxWeaviate
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