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DBMS > GridDB vs. HEAVY.AI vs. Tibero vs. Typesense

System Properties Comparison GridDB vs. HEAVY.AI vs. Tibero vs. Typesense

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonTibero  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA secure RDBMS, designed for easy portability from OracleA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelTime Series DBMSRelational DBMSRelational DBMSSearch engine
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
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score1.78
Rank#140  Overall
#64  Relational DBMS
Score0.79
Rank#210  Overall
#14  Search engines
Websitegriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
us.tmaxsoft.com/­products/­tiberotypesense.org
Technical documentationdocs.griddb.netdocs.heavy.aitechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.htmltypesense.org/­docs
DeveloperToshiba CorporationHEAVY.AI, Inc.TmaxSoft
Initial release2013201620032015
Current release5.1, August 20225.10, January 20226, April 2015
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; enterprise edition availablecommercialOpen Source infoGPL V3
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++C++ and CUDAC and AssemblerC++
Server operating systemsLinuxLinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
Data schemeyesyesyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyes 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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesyesno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
RESTful HTTP API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresnonoPersistent Stored Procedure (PSM)no
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinhorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationMulti-source replication
Source-replica replication
Multi-source replication using RAFT
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACIDno
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.yesyesno infoplanned for next versionyes
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardfine grained access rights according to SQL-standard (SQL 92, SQL 99)
More information provided by the system vendor
GridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022TiberoTypesense
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
GridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022TiberoTypesense
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