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DBMS > GridDB vs. Hypertable vs. Solr vs. Trafodion

System Properties Comparison GridDB vs. Hypertable vs. Solr vs. Trafodion

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHypertable  Xexclude from comparisonSolr  Xexclude from comparisonTrafodion  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataAn open source BigTable implementation based on distributed file systems such as HadoopA widely used distributed, scalable search engine based on Apache LuceneTransactional SQL-on-Hadoop DBMS
Primary database modelTime Series DBMSWide column storeSearch 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
Websitegriddb.netsolr.apache.orgtrafodion.apache.org
Technical documentationdocs.griddb.netsolr.apache.org/­resources.htmltrafodion.apache.org/­documentation.html
DeveloperToshiba CorporationHypertable Inc.Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release2013200920062014
Current release5.1, August 20220.9.8.11, March 20169.5.0, February 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++JavaC++, Java
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampnoyes infosupports customizable data types and automatic typingyes
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.noyesno
Secondary indexesyesrestricted infoonly exact value or prefix value scansyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
C++ API
Thrift
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnonoJava pluginsJava Stored Procedures
Triggersyesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor on file system levelyesyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per databasenoyesfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBHypertableSolrTrafodion
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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GridDBHypertableSolrTrafodion
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