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

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

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonGridDB  Xexclude from comparisonSequoiadb  Xexclude from comparisonSphinx  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 DataNewSQL database with distributed OLTP and SQLOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineTime Series DBMSDocument store
Relational DBMS
Search engine
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­cloudsearchgriddb.netwww.sequoiadb.comsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.griddb.netwww.sequoiadb.com/­en/­index.php?m=Files&a=indexsphinxsearch.com/­docs
DeveloperAmazonToshiba CorporationSequoiadb Ltd.Sphinx Technologies Inc.
Initial release2012201320132001
Current release5.1, August 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoServer: AGPL; Client: Apache V2Open Source infoGPL version 2, commercial licence available
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++C++
Server operating systemshostedLinuxLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infooid, date, timestamp, binary, regexno
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
Secondary indexesyes infoall search fields are automatically indexedyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsHTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
proprietary protocol using JSONProprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C++
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoJavaScriptno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSSource-replica replicationSource-replica replicationnone
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 containersEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users can be defined per databasesimple password-based access controlno
More information provided by the system vendor
Amazon CloudSearchGridDBSequoiadbSphinx
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 CloudSearchGridDBSequoiadbSphinx
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