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DBMS > GridDB vs. HBase vs. MaxDB vs. Spark SQL

System Properties Comparison GridDB vs. HBase vs. MaxDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHBase  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTableA robust and reliable RDBMS optimized to run all major SAP solutionsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSWide column storeRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.32
Rank#112  Overall
#55  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegriddb.nethbase.apache.orgmaxdb.sap.comspark.apache.org/­sql
Technical documentationdocs.griddb.nethbase.apache.org/­book.htmlmaxdb.sap.com/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetSAP, acquired from Software AG (Adabas-D) in 1997Apache Software Foundation
Initial release2013200819842014
Current release5.1, August 20222.3.4, January 20217.9.10.12, February 20243.5.0 ( 2.13), September 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 2commercial infoLimited community edition freeOpen Source infoApache 2.0
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++JavaC++Scala
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
AIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
WebDAV
JDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
Java
Perl
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayesno
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelSingle row ACID (across millions of columns)ACIDno
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 databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standardno
More information provided by the system vendor
GridDBHBaseMaxDB infoformerly named Adabas-DSpark 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
GridDBHBaseMaxDB infoformerly named Adabas-DSpark SQL
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