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DBMS > EsgynDB vs. LMDB vs. Microsoft Azure AI Search vs. Weaviate

System Properties Comparison EsgynDB vs. LMDB vs. Microsoft Azure AI Search vs. Weaviate

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonLMDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA high performant, light-weight, embedded key-value database librarySearch-as-a-service for web and mobile app developmentAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSKey-value storeSearch engineVector DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score5.59
Rank#63  Overall
#7  Search engines
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.esgyn.cnwww.symas.com/­symas-embedded-database-lmdbazure.microsoft.com/­en-us/­services/­searchgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.lmdb.tech/­doclearn.microsoft.com/­en-us/­azure/­searchweaviate.io/­developers/­weaviate
DeveloperEsgynSymasMicrosoftWeaviate B.V.
Initial release2015201120152019
Current release0.9.32, January 2024V11.19, May 2023
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaCGo
Server operating systemsLinuxLinux
Unix
Windows
hosted
Data schemeyesschema-freeyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyes 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.nononono
Secondary indexesyesnoyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesnonoGraphQL is used as query language
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIGraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
C#
Java
JavaScript
Python
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnoneyes infoImplicit feature of the cloud serviceyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyes infousing Azure authenticationAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
EsgynDBLMDBMicrosoft Azure AI SearchWeaviate
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
EsgynDBLMDBMicrosoft Azure AI SearchWeaviate
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