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DBMS > Databend vs. GridDB vs. HBase vs. MaxDB

System Properties Comparison Databend vs. GridDB vs. HBase vs. MaxDB

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGridDB  Xexclude from comparisonHBase  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityScalable 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 solutions
Primary database modelRelational DBMSTime Series DBMSWide column storeRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score2.26
Rank#114  Overall
#55  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
griddb.nethbase.apache.orgmaxdb.sap.com
Technical documentationdocs.databend.comdocs.griddb.nethbase.apache.org/­book.htmlmaxdb.sap.com/­documentation
DeveloperDatabend LabsToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetSAP, acquired from Software AG (Adabas-D) in 1997
Initial release2021201320081984
Current release1.0.59, April 20235.1, August 20222.3.4, January 20217.9.10.12, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open 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 free
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustC++JavaC++
Server operating systemshosted
Linux
macOS
LinuxLinux
Unix
Windows infousing Cygwin
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyes
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 indexesnoyesnoyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)noyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
WebDAV
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
Java
Perl
PHP
Python
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID at container levelSingle row ACID (across millions of columns)ACID
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 controlUsers with fine-grained authorization concept, user rolesAccess 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-standard
More information provided by the system vendor
DatabendGridDBHBaseMaxDB infoformerly named Adabas-D
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
DatabendGridDBHBaseMaxDB infoformerly named Adabas-D
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