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DBMS > Databend vs. GBase vs. GridDB vs. HBase

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

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGBase  Xexclude from comparisonGridDB  Xexclude from comparisonHBase  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 complexityWidely 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 DataWide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelRelational DBMSRelational DBMSTime Series DBMSWide column store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.gbase.cngriddb.nethbase.apache.org
Technical documentationdocs.databend.comdocs.griddb.nethbase.apache.org/­book.html
DeveloperDatabend LabsGeneral Data Technology Co., Ltd.Toshiba CorporationApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2021200420132008
Current release1.0.59, April 2023GBase 8a, GBase 8s, GBase 8c5.1, August 20222.3.4, January 2021
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 version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustC, Java, PythonC++Java
Server operating systemshosted
Linux
macOS
LinuxLinuxLinux
Unix
Windows infousing Cygwin
Data schemeyesyesyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVRO
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 indexesnoyesyesno
SQL infoSupport of SQLyesStandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
ADO.NET
C API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoCoprocessors in Java
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesSource-replica replicationMulti-source 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 jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACID at container levelSingle row ACID (across millions of columns)
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.yesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesyesAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
DatabendGBaseGridDBHBase
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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DatabendGBaseGridDBHBase
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