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DBMS > Graph Engine vs. GridDB vs. HEAVY.AI vs. Spark SQL

System Properties Comparison Graph Engine vs. GridDB vs. HEAVY.AI vs. Spark SQL

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonGridDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineScalable 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 hardwareSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
Key-value store
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.graphengine.iogriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
spark.apache.org/­sql
Technical documentationwww.graphengine.io/­docs/­manualdocs.griddb.netdocs.heavy.aispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftToshiba CorporationHEAVY.AI, Inc.Apache Software Foundation
Initial release2010201320162014
Current release5.1, August 20225.10, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen 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 infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CC++C++ and CUDAScala
Server operating systems.NETLinuxLinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes 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.nononono
Secondary indexesyesnono
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Supported programming languagesC#
C++
F#
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnonono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoRound robinyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
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 databasefine grained access rights according to SQL-standardno
More information provided by the system vendor
Graph Engine infoformer name: TrinityGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Spark SQL
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
Graph Engine infoformer name: TrinityGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Spark SQL
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