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DBMS > Amazon CloudSearch vs. GBase vs. GridDB vs. Sphinx vs. TimescaleDB

System Properties Comparison Amazon CloudSearch vs. GBase vs. GridDB vs. Sphinx vs. TimescaleDB

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonGBase  Xexclude from comparisonGridDB  Xexclude from comparisonSphinx  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudAn analytical database for business intelligence with large customers in China.Scalable in-memory time series database optimized for IoT and Big DataOpen source search engine for searching in data from different sources, e.g. relational databasesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelSearch engineRelational DBMSTime Series DBMSSearch engineTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.87
Rank#140  Overall
#12  Search engines
Score1.04
Rank#190  Overall
#88  Relational DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websiteaws.amazon.com/­cloudsearchwww.gbase.cngriddb.netsphinxsearch.comwww.timescale.com
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.griddb.netsphinxsearch.com/­docsdocs.timescale.com
DeveloperAmazonToshiba CorporationSphinx Technologies Inc.Timescale
Initial release2012201320012017
Current releaseGBase 8a5.1, August 20223.5.1, February 20232.13.0, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C
Server operating systemshostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyes
Secondary indexesyes infoall search fields are automatically indexedyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsHTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnononouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesnoyes
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 supportedyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSSource-replica replicationnoneSource-replica replication with hot standby and reads on replicas info
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
Foreign keys infoReferential integritynononoyes
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.yesno
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users can be defined per databasenofine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon CloudSearchGBaseGridDBSphinxTimescaleDB
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 CloudSearchGBaseGridDBSphinxTimescaleDB
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