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DBMS > Apache IoTDB vs. Cubrid vs. HBase vs. QuestDB

System Properties Comparison Apache IoTDB vs. Cubrid vs. HBase vs. QuestDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCubrid  Xexclude from comparisonHBase  Xexclude from comparisonQuestDB  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 FlinkCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPWide-column store based on Apache Hadoop and on concepts of BigTableA high performance open source SQL database for time series data
Primary database modelTime Series DBMSRelational DBMSWide column storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websiteiotdb.apache.orgcubrid.com (korean)
cubrid.org (english)
hbase.apache.orgquestdb.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcubrid.org/­manualshbase.apache.org/­book.htmlquestdb.io/­docs
DeveloperApache Software FoundationCUBRID Corporation, CUBRID FoundationApache Software Foundation infoApache top-level project, originally developed by PowersetQuestDB Technology Inc
Initial release2018200820082014
Current release1.1.0, April 202311.0, January 20212.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache version 2Open 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 languageJavaC, C++, JavaJavaJava (Zero-GC), C++, Rust
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
Linux
Unix
Windows infousing Cygwin
Linux
macOS
Windows
Data schemeyesyesschema-free, schema definition possibleyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesoptions 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 indexesyesyesnono
SQL infoSupport of SQLSQL-like query languageyesnoSQL with time-series extensions
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
OLE DB
Java API
RESTful HTTP API
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyesJava Stored Proceduresyes infoCoprocessors in Javano
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)ACID 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.yesnoyesyes infothrough memory mapped files
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
Apache IoTDBCubridHBaseQuestDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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