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DBMS > Apache IoTDB vs. InfluxDB vs. Solr vs. WakandaDB

System Properties Comparison Apache IoTDB vs. InfluxDB vs. Solr vs. WakandaDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonInfluxDB  Xexclude from comparisonSolr  Xexclude from comparisonWakandaDB  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 FlinkDBMS for storing time series, events and metricsA widely used distributed, scalable search engine based on Apache LuceneWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelTime Series DBMSTime Series DBMSSearch engineObject oriented DBMS
Secondary database modelsSpatial DBMS infowith GEO packageSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websiteiotdb.apache.orgwww.influxdata.com/­products/­influxdb-overviewsolr.apache.orgwakanda.github.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.influxdata.com/­influxdbsolr.apache.org/­resources.htmlwakanda.github.io/­doc
DeveloperApache Software FoundationApache Software FoundationWakanda SAS
Initial release2018201320062012
Current release1.1.0, April 20232.7.6, April 20249.6.1, May 20242.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT-License; commercial enterprise version availableOpen Source infoApache Version 2Open Source infoAGPLv3, extended commercial license available
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 languageJavaGoJavaC++, JavaScript
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X infothrough Homebrew
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyes infosupports customizable data types and automatic typingyes
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.nonoyesno
Secondary indexesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL-like query languageSolr Parallel SQL Interfaceno
APIs and other access methodsJDBC
Native API
HTTP API
JSON over UDP
Java API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
JavaScript
Server-side scripts infoStored proceduresyesnoJava pluginsyes
Triggersyesnoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoin enterprise version onlyShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor infoin enterprise version onlyyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACID
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 infoDepending on used storage engineyesno
User concepts infoAccess controlyessimple rights management via user accountsyesyes
More information provided by the system vendor
Apache IoTDBInfluxDBSolrWakandaDB
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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