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DBMS > Apache IoTDB vs. HBase vs. InfluxDB vs. SQLite

System Properties Comparison Apache IoTDB vs. HBase vs. InfluxDB vs. SQLite

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHBase  Xexclude from comparisonInfluxDB  Xexclude from comparisonSQLite  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 FlinkWide-column store based on Apache Hadoop and on concepts of BigTableDBMS for storing time series, events and metricsWidely used embeddable, in-process RDBMS
Primary database modelTime Series DBMSWide column storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score26.56
Rank#28  Overall
#1  Time Series DBMS
Score116.01
Rank#10  Overall
#7  Relational DBMS
Websiteiotdb.apache.orghbase.apache.orgwww.influxdata.com/­products/­influxdb-overviewwww.sqlite.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhbase.apache.org/­book.htmldocs.influxdata.com/­influxdbwww.sqlite.org/­docs.html
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by PowersetDwayne Richard Hipp
Initial release2018200820132000
Current release1.1.0, April 20232.3.4, January 20212.7.5, January 20243.45.3  (15 April 2024), April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoMIT-License; commercial enterprise version availableOpen Source infoPublic Domain
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 languageJavaJavaGoC
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows infousing Cygwin
Linux
OS X infothrough Homebrew
server-less
Data schemeyesschema-free, schema definition possibleschema-freeyes infodynamic column types
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVRONumeric data and Stringsyes infonot rigid because of 'dynamic typing' concept.
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 indexesyesnonoyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languageyes infoSQL-92 is not fully supported
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
Thrift
HTTP API
JSON over UDP
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
Server-side scripts infoStored proceduresyesyes infoCoprocessors in Javanono
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoin enterprise version onlynone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
selectable replication factor infoin enterprise version onlynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)noACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infovia file-system locks
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 infoDepending on used storage engineyes
User concepts infoAccess controlyesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple rights management via user accountsno
More information provided by the system vendor
Apache IoTDBHBaseInfluxDBSQLite
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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