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DBMS > GridDB vs. Solr vs. Sphinx vs. SQream DB

System Properties Comparison GridDB vs. Solr vs. Sphinx vs. SQream DB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databasesa GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelTime Series DBMSSearch engineSearch engineRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitegriddb.netsolr.apache.orgsphinxsearch.comsqream.com
Technical documentationdocs.griddb.netsolr.apache.org/­resources.htmlsphinxsearch.com/­docsdocs.sqream.com
DeveloperToshiba CorporationApache Software FoundationSphinx Technologies Inc.SQream Technologies
Initial release2013200620012017
Current release5.1, August 20229.6.0, April 20243.5.1, February 20232022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++C++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes infosupports customizable data types and automatic typingnoyes, ANSI Standard SQL 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 indexesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)Solr Parallel SQL InterfaceSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
Proprietary protocol.Net
JDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoJava pluginsnouser defined functions in Python
Triggersyesyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container leveloptimistic lockingnoACID
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 controlAccess rights for users can be defined per databaseyesno
More information provided by the system vendor
GridDBSolrSphinxSQream DB
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
GridDBSolrSphinxSQream DB
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