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DBMS > GridDB vs. HEAVY.AI vs. SWC-DB vs. Teradata Aster

System Properties Comparison GridDB vs. HEAVY.AI vs. SWC-DB vs. Teradata Aster

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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 comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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 high performance, scalable Wide Column DBMSPlatform for big data analytics on multistructured data sources and types
Primary database modelTime Series DBMSRelational DBMSWide column storeRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSTime Series DBMS
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
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitegriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.griddb.netdocs.heavy.ai
DeveloperToshiba CorporationHEAVY.AI, Inc.Alex KashirinTeradata
Initial release2013201620202005
Current release5.1, August 20225.10, January 20220.5, April 2021
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 V3commercial
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 systemsLinuxLinuxLinuxLinux
Data schemeyesyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nononoyes infoin Aster File Store
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Proprietary protocol
Thrift
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnononoR packages
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACID
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 databasefine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022SWC-DB infoSuper Wide Column DatabaseTeradata Aster
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 2022SWC-DB infoSuper Wide Column DatabaseTeradata Aster
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