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DBMS > Apache IoTDB vs. Solr vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  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 FlinkA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgsolr.apache.orgspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationApache Software FoundationApache Software Foundation
Initial release201820062014
Current release1.1.0, April 20239.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes 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.noyesno
Secondary indexesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languageSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesJava pluginsno
Triggersyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesyesno

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More resources
Apache IoTDBSolrSpark SQL
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