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DBMS > Amazon CloudSearch vs. GridDB vs. Sphinx vs. Stardog

System Properties Comparison Amazon CloudSearch vs. GridDB vs. Sphinx vs. Stardog

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonGridDB  Xexclude from comparisonSphinx  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudScalable in-memory time series database optimized for IoT and Big DataOpen source search engine for searching in data from different sources, e.g. relational databasesEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelSearch engineTime Series DBMSSearch engineGraph DBMS
RDF store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­cloudsearchgriddb.netsphinxsearch.comwww.stardog.com
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.griddb.netsphinxsearch.com/­docsdocs.stardog.com
DeveloperAmazonToshiba CorporationSphinx Technologies Inc.Stardog-Union
Initial release2012201320012010
Current release5.1, August 20223.5.1, February 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2, commercial licence availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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++C++Java
Server operating systemshostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesyesyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampnoyes
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.nono infoImport/export of XML data possible
Secondary indexesyes infoall search fields are automatically indexedyesyes infofull-text index on all search fieldsyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (SphinxQL)Yes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsHTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocolGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnononouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSSource-replica replicationnoneMulti-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 consistency within container, eventual consistency across containersImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnoACID
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.yesyes
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users can be defined per databasenoAccess rights for users and roles
More information provided by the system vendor
Amazon CloudSearchGridDBSphinxStardog
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 CloudSearchGridDBSphinxStardog
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