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DBMS > EsgynDB vs. HEAVY.AI vs. Sphinx vs. Weaviate

System Properties Comparison EsgynDB vs. HEAVY.AI vs. Sphinx vs. Weaviate

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSphinx  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOpen 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 modelRelational DBMSRelational DBMSSearch engineVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.esgyn.cngithub.com/­heavyai/­heavydb
www.heavy.ai
sphinxsearch.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.heavy.aisphinxsearch.com/­docsweaviate.io/­developers/­weaviate
DeveloperEsgynHEAVY.AI, Inc.Sphinx Technologies Inc.Weaviate B.V.
Initial release2015201620012019
Current release5.10, January 20223.5.1, February 20231.19, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen 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 languageC++, JavaC++ and CUDAC++Go
Server operating systemsLinuxLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes, 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 indexesyesnoyes 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 SQLyesyesSQL-like query language (SphinxQL)GraphQL is used as query language
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
Vega
Proprietary protocolGraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetAll languages supporting JDBC/ODBC/Thrift
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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 controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
EsgynDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022SphinxWeaviate
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
EsgynDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022SphinxWeaviate
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