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DBMS > Cubrid vs. GridDB vs. IBM Db2 vs. JanusGraph vs. Vertica

System Properties Comparison Cubrid vs. GridDB vs. IBM Db2 vs. JanusGraph vs. Vertica

Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonGridDB  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPScalable in-memory time series database optimized for IoT and Big DataCommon in IBM host environments, 2 different versions for host and Windows/LinuxA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsKey-value store
Relational DBMS
Document store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitecubrid.com (korean)
cubrid.org (english)
griddb.netwww.ibm.com/­products/­db2janusgraph.orgwww.vertica.com
Technical documentationcubrid.org/­manualsdocs.griddb.netwww.ibm.com/­docs/­en/­db2docs.janusgraph.orgvertica.com/­documentation
DeveloperCUBRID Corporation, CUBRID FoundationToshiba CorporationIBMLinux Foundation; originally developed as Titan by AureliusOpenText infopreviously Micro Focus and Hewlett Packard
Initial release200820131983 infohost version20172005
Current release11.0, January 20215.1, August 202212.1, October 20160.6.3, February 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree version is availableOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaC++C and C++JavaC++
Server operating systemsLinux
Windows
LinuxAIX
HP-UX
Linux
Solaris
Windows
z/OS
Linux
OS X
Unix
Windows
Linux
Data schemeyesyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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.nononono
Secondary indexesyesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)yesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
Clojure
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresnoyesyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoonly with Windows/Unix/Linux Versionyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)horizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyes infowith separate tools (MQ, InfoSphere)yesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoyes infovia Faunus, a graph analytics engineno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databasefine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
CubridGridDBIBM Db2 infoformerly named DB2 or IBM Database 2JanusGraph infosuccessor of TitanVertica infoOpenText™ Vertica™
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
CubridGridDBIBM Db2 infoformerly named DB2 or IBM Database 2JanusGraph infosuccessor of TitanVertica infoOpenText™ Vertica™
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