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DBMS > GridDB vs. HBase vs. HEAVY.AI vs. JaguarDB

System Properties Comparison GridDB vs. HBase vs. HEAVY.AI vs. JaguarDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHBase  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonJaguarDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTableA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwarePerformant, highly scalable DBMS for AI and IoT applications
Primary database modelTime Series DBMSWide column storeRelational DBMSKey-value store
Vector 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Websitegriddb.nethbase.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.jaguardb.com
Technical documentationdocs.griddb.nethbase.apache.org/­book.htmldocs.heavy.aiwww.jaguardb.com/­support.html
DeveloperToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetHEAVY.AI, Inc.DataJaguar, Inc.
Initial release2013200820162015
Current release5.1, August 20222.3.4, January 20215.10, January 20223.3 July 2023
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 2Open Source infoApache Version 2; enterprise edition availableOpen Source infoGPL V3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++ and CUDAC++ infothe server part. Clients available in other languages
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
LinuxLinux
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyesyes
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 indexesyesnonoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggers
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javanono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelSingle row ACID (across millions of columns)nono
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.yesyesyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standardrights management via user accounts
More information provided by the system vendor
GridDBHBaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022JaguarDB
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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GridDBHBaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022JaguarDB
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