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DBMS > Apache IoTDB vs. GBase vs. GridDB vs. Spark SQL

System Properties Comparison Apache IoTDB vs. GBase vs. GridDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGBase  Xexclude from comparisonGridDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Scalable in-memory time series database optimized for IoT and Big DataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgwww.gbase.cngriddb.netspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.griddb.netspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGeneral Data Technology Co., Ltd.Toshiba CorporationApache Software Foundation
Initial release2018200420132014
Current release1.1.0, April 2023GBase 8a, GBase 8s, GBase 8c5.1, August 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also 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 languageJavaC, Java, PythonC++Scala
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.noyesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageStandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
ADO.NET
C API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsnono
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning (by range, list and hash) and vertical partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelno
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
User concepts infoAccess controlyesyesAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache IoTDBGBaseGridDBSpark 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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Apache IoTDBGBaseGridDBSpark SQL
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