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DBMS > Coveo vs. GridDB vs. Infobright vs. Sphinx

System Properties Comparison Coveo vs. GridDB vs. Infobright vs. Sphinx

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonGridDB  Xexclude from comparisonInfobright  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentScalable in-memory time series database optimized for IoT and Big DataHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineTime Series DBMSRelational DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.11
Rank#118  Overall
#11  Search engines
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.coveo.comgriddb.netignitetech.com/­softwarelibrary/­infobrightdbsphinxsearch.com
Technical documentationdocs.coveo.comdocs.griddb.netsphinxsearch.com/­docs
DeveloperCoveoToshiba CorporationIgnite Technologies Inc.; formerly InfoBright Inc.Sphinx Technologies Inc.
Initial release2012201320052001
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 availablecommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open 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++CC++
Server operating systemshostedLinuxLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesno
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.nonono
Secondary indexesyesyesno infoKnowledge Grid Technology used insteadyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
Java
JavaScript
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesyesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-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 ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID at container levelACIDno
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.yesyes
User concepts infoAccess controlgranular access controls, API key management, content filtersAccess rights for users can be defined per databasefine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesno
More information provided by the system vendor
CoveoGridDBInfobrightSphinx
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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More resources
CoveoGridDBInfobrightSphinx
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