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DBMS > Apache IoTDB vs. Solr vs. Speedb vs. Sphinx

System Properties Comparison Apache IoTDB vs. Solr vs. Speedb vs. Sphinx

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonSolr  Xexclude from comparisonSpeedb  Xexclude from comparisonSphinx  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 LuceneAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSSearch engineKey-value storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.26
Rank#310  Overall
#45  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteiotdb.apache.orgsolr.apache.orgwww.speedb.iosphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperApache Software FoundationApache Software FoundationSpeedbSphinx Technologies Inc.
Initial release2018200620202001
Current release1.1.0, April 20239.6.1, May 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoApache Version 2.0; commercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C++
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
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-freeyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingnono
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 indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageSolr Parallel SQL InterfacenoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP/JSON API
Proprietary protocol
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
C
C++
Go
Java
Perl
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesJava pluginsnono
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)Shardinghorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesyesnono
More information provided by the system vendor
Apache IoTDBSolrSpeedbSphinx
Specific characteristicsSpeedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesSpeedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» more
Licensing and pricing modelsOpen source - Speedb OSS is released under an Apache license and can be found on...
» more

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Apache IoTDBSolrSpeedbSphinx
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