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DBMS > GridDB vs. HBase vs. Linter vs. QuestDB

System Properties Comparison GridDB vs. HBase vs. Linter vs. QuestDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHBase  Xexclude from comparisonLinter  Xexclude from comparisonQuestDB  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 BigTableRDBMS for high security requirementsA high performance open source SQL database for time series data
Primary database modelTime Series DBMSWide column storeRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSRelational 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
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitegriddb.nethbase.apache.orglinter.ruquestdb.io
Technical documentationdocs.griddb.nethbase.apache.org/­book.htmlquestdb.io/­docs
DeveloperToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by Powersetrelex.ruQuestDB Technology Inc
Initial release2013200819902014
Current release5.1, August 20222.3.4, January 2021
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 2commercialOpen 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 and C++Java (Zero-GC), C++, Rust
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS
Windows
Data schemeyesschema-free, schema definition possibleyesyes infoschema-free via InfluxDB Line Protocol
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 with time-series extensions
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyImmediate 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)ACIDACID for single-table writes
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.yesyesyes infothrough memory mapped files
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-standard
More information provided by the system vendor
GridDBHBaseLinterQuestDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GridDBHBaseLinterQuestDB
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