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DBMS > Apache IoTDB vs. Drizzle vs. Solr vs. Typesense

System Properties Comparison Apache IoTDB vs. Drizzle vs. Solr vs. Typesense

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonSolr  Xexclude from comparisonTypesense  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
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 FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A widely used distributed, scalable search engine based on Apache LuceneA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelTime Series DBMSRelational DBMSSearch engineSearch 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
Score0.76
Rank#219  Overall
#14  Search engines
Websiteiotdb.apache.orgsolr.apache.orgtypesense.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsolr.apache.org/­resources.htmltypesense.org/­docs
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerApache Software Foundation
Initial release2018200820062015
Current release1.1.0, April 20237.2.4, September 20129.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infoApache Version 2Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyes 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.noyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsSolr Parallel SQL Interfaceno
APIs and other access methodsJDBC
Native API
JDBCJava API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresyesnoJava pluginsno
Triggersyesno infohooks for callbacks inside the server can be used.yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
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
yesMulti-source replication using RAFT
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 Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingno
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.yesyesyes
User concepts infoAccess controlyesPluggable authentication mechanisms infoe.g. LDAP, HTTPyes

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More resources
Apache IoTDBDrizzleSolrTypesense
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