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DBMS > GridDB vs. Sphinx vs. Stardog vs. Valentina Server

System Properties Comparison GridDB vs. Sphinx vs. Stardog vs. Valentina Server

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonSphinx  Xexclude from comparisonStardog  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionScalable 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 virtualizationObject-relational database and reports server
Primary database modelTime Series DBMSSearch engineGraph DBMS
RDF store
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitegriddb.netsphinxsearch.comwww.stardog.comwww.valentina-db.net
Technical documentationdocs.griddb.netsphinxsearch.com/­docsdocs.stardog.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperToshiba CorporationSphinx Technologies Inc.Stardog-UnionParadigma Software
Initial release2013200120101999
Current release5.1, August 20223.5.1, February 20237.3.0, May 20205.7.5
License infoCommercial or Open SourceOpen 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/studentscommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemsLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampnoyesyes
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 indexesyesyes infofull-text index on all search fieldsyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (SphinxQL)Yes, compatible with all major SQL variants through dedicated BI/SQL Serveryes
APIs and other access methodsJDBC
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
ODBC
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
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnonouser defined functions and aggregates, HTTP Server extensions in Javayes
Triggersyesnoyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users can be defined per databasenoAccess rights for users and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBSphinxStardogValentina 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
GridDBSphinxStardogValentina Server
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