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DBMS > GridDB vs. HEAVY.AI vs. Manticore Search vs. Realm

System Properties Comparison GridDB vs. HEAVY.AI vs. Manticore Search vs. Realm

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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 comparisonManticore Search  Xexclude from comparisonRealm  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 hardwareMulti-storage database for search, including full-text search.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelTime Series DBMSRelational DBMSSearch engineDocument store
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Score7.41
Rank#52  Overall
#8  Document stores
Websitegriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
manticoresearch.comrealm.io
Technical documentationdocs.griddb.netdocs.heavy.aimanual.manticoresearch.comrealm.io/­docs
DeveloperToshiba CorporationHEAVY.AI, Inc.Manticore SoftwareRealm, acquired by MongoDB in May 2019
Initial release2013201620172014
Current release5.1, August 20225.10, January 20226.0, February 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 2; enterprise edition availableOpen Source infoGPL version 2Open Source
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++
Server operating systemsLinuxLinuxFreeBSD
Linux
macOS
Windows
Android
Backend: server-less
iOS
Windows
Data schemeyesyesFixed schemayes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XMLno
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like query languageno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresnonouser defined functionsno inforuns within the applications so server-side scripts are unnecessary
Triggersyesnonoyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationSynchronous replication based on Galera librarynone
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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoIn-Memory realm
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardnoyes
More information provided by the system vendor
GridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Manticore SearchRealm
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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GridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Manticore SearchRealm
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