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DBMS > GridDB vs. InfinityDB vs. RDF4J vs. Rockset

System Properties Comparison GridDB vs. InfinityDB vs. RDF4J vs. Rockset

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonInfinityDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA Java embedded Key-Value Store which extends the Java Map interfaceRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelTime Series DBMSKey-value storeRDF storeDocument store
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.79
Rank#211  Overall
#35  Document stores
Websitegriddb.netboilerbay.comrdf4j.orgrockset.com
Technical documentationdocs.griddb.netboilerbay.com/­infinitydb/­manualrdf4j.org/­documentationdocs.rockset.com
DeveloperToshiba CorporationBoiler Bay Inc.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Rockset
Initial release2013200220042019
Current release5.1, August 20224.0
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaC++
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Unix
Windows
hosted
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesdynamic typing
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 infoingestion from XML files supported
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesall fields are automatically indexed
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)nonoRead-only SQL queries, including JOINs
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
HTTP REST
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaJava
PHP
Python
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyesno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneyes
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 infoREAD-COMMITTED or SERIALIZEDEventual Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACID infoOptimistic locking for transactions; no isolation for bulk loadsACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users can be defined per databasenonoAccess rights for users and organizations can be defined via Rockset console
More information provided by the system vendor
GridDBInfinityDBRDF4J infoformerly known as SesameRockset
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
GridDBInfinityDBRDF4J infoformerly known as SesameRockset
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