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DBMS > GridDB vs. GridGain vs. Stardog vs. Yanza

System Properties Comparison GridDB vs. GridGain vs. Stardog vs. Yanza

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonGridGain  Xexclude from comparisonStardog  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataGridGain is an in-memory computing platform, built on Apache IgniteEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Graph DBMS
RDF store
Time Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.00
Rank#137  Overall
#11  Time Series DBMS
Score1.59
Rank#158  Overall
#26  Key-value stores
#73  Relational DBMS
Score2.03
Rank#136  Overall
#12  Graph DBMS
#6  RDF stores
Websitegriddb.netwww.gridgain.comwww.stardog.comyanza.com
Technical documentationdocs.griddb.netwww.gridgain.com/­docs/­index.htmldocs.stardog.com
DeveloperToshiba CorporationGridGain Systems, Inc.Stardog-UnionYanza
Initial release2013200720102015
Current release5.1, August 2022GridGain 8.5.17.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, C++, .NetJava
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Windows
Data schemeyesyesschema-free and OWL/RDFS-schema supportschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesno
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 infoImport/export of XML data possibleno
Secondary indexesyesyesyes infosupports real-time indexing in full-text and geospatialno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLYes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
HTTP API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)user defined functions and aggregates, HTTP Server extensions in Javano
Triggersyesyes (cache interceptors and events)yes infovia event handlersyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)Multi-source replication in HA-Clusternone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynonoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACIDno
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.yesyesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsAccess rights for users and rolesno
More information provided by the system vendor
GridDBGridGainStardogYanza
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
GridDBGridGainStardogYanza
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