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DBMS > Amazon Aurora vs. GridDB vs. Stardog vs. Valentina Server

System Properties Comparison Amazon Aurora vs. GridDB vs. Stardog vs. Valentina Server

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGridDB  Xexclude from comparisonStardog  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonScalable in-memory time series database optimized for IoT and Big DataEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationObject-relational database and reports server
Primary database modelRelational DBMSTime Series DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websiteaws.amazon.com/­rds/­auroragriddb.netwww.stardog.comwww.valentina-db.net
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.griddb.netdocs.stardog.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperAmazonToshiba CorporationStardog-UnionParadigma Software
Initial release2015201320101999
Current release5.1, August 20227.3.0, May 20205.7.5
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial
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++Java
Server operating systemshostedLinuxLinux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.yesnono infoImport/export of XML data possible
Secondary indexesyesyesyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)Yes, compatible with all major SQL variants through dedicated BI/SQL Serveryes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyesnouser defined functions and aggregates, HTTP Server extensions in Javayes
Triggersyesyesyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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-standardAccess rights for users can be defined per databaseAccess rights for users and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon AuroraGridDBStardogValentina Server
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» 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 AuroraGridDBStardogValentina Server
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