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DBMS > Amazon Aurora vs. HEAVY.AI vs. LMDB vs. Weaviate

System Properties Comparison Amazon Aurora vs. HEAVY.AI vs. LMDB vs. Weaviate

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLMDB  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA high performant, light-weight, embedded key-value database libraryAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSRelational DBMSKey-value storeVector DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.84
Rank#44  Overall
#28  Relational DBMS
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score1.94
Rank#120  Overall
#20  Key-value stores
Score1.48
Rank#149  Overall
#8  Vector DBMS
Websiteaws.amazon.com/­rds/­auroragithub.com/­heavyai/­heavydb
www.heavy.ai
www.symas.com/­symas-embedded-database-lmdbgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.heavy.aiwww.lmdb.tech/­docweaviate.io/­developers/­weaviate
DeveloperAmazonHEAVY.AI, Inc.SymasWeaviate B.V.
Initial release2015201620112019
Current release5.10, January 20220.9.32, January 20241.19, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen SourceOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDACGo
Server operating systemshostedLinuxLinux
Unix
Windows
Data schemeyesyesschema-freeyes, 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.yesnonono
Secondary indexesyesnonoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesyesnoGraphQL is used as query language
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
Vega
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBC/Thrift
Python
.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
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyesnonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoRound robinnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
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 dataACIDnoACIDno
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.yesyesyesyes
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
Amazon AuroraHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LMDBWeaviate
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
Amazon AuroraHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LMDBWeaviate
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