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DBMS > GridDB vs. HugeGraph vs. TimescaleDB vs. Trafodion

System Properties Comparison GridDB vs. HugeGraph vs. TimescaleDB vs. Trafodion

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTrafodion  Xexclude from comparison
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 DataA fast-speed and highly-scalable Graph DBMSA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTransactional SQL-on-Hadoop DBMS
Primary database modelTime Series DBMSGraph DBMSTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score0.15
Rank#339  Overall
#33  Graph DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websitegriddb.netgithub.com/­hugegraph
hugegraph.apache.org
www.timescale.comtrafodion.apache.org
Technical documentationdocs.griddb.nethugegraph.apache.org/­docsdocs.timescale.comtrafodion.apache.org/­documentation.html
DeveloperToshiba CorporationBaiduTimescaleApache Software Foundation, originally developed by HP
Initial release2013201820172014
Current release5.1, August 20220.92.13.0, November 20232.3.0, 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 infoApache Version 2.0Open Source infoApache 2.0Open 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++JavaCC++, Java
Server operating systemsLinuxLinux
macOS
Unix
Linux
OS X
Windows
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyesno
Secondary indexesyesyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Groovy
Java
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellJava Stored Procedures
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication with hot standby and reads on replicas infoyes, 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 jobsvia hugegraph-sparknoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACIDACID
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.yesyesnono
User concepts infoAccess controlAccess rights for users can be defined per databaseUsers, roles and permissionsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBHugeGraphTimescaleDBTrafodion
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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GridDBHugeGraphTimescaleDBTrafodion
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