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DBMS > Apache IoTDB vs. Dragonfly vs. ObjectBox vs. Solr

System Properties Comparison Apache IoTDB vs. Dragonfly vs. ObjectBox vs. Solr

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDragonfly  Xexclude from comparisonObjectBox  Xexclude from comparisonSolr  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 drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceExtremely fast embedded database for small devices, IoT and MobileA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSKey-value storeObject oriented DBMSSearch engine
Secondary database modelsTime Series DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
objectbox.iosolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.dragonflydb.io/­docsdocs.objectbox.iosolr.apache.org/­resources.html
DeveloperApache Software FoundationDragonflyDB team and community contributorsObjectBox LimitedApache Software Foundation
Initial release2018202320172006
Current release1.1.0, April 20231.0, March 20239.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSL 1.1Open Source infoApache License 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C and C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAndroid
iOS
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesscheme-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
Proprietary protocol infoRESP - REdis Serialization ProtocolProprietary native APIJava API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesLuanoJava plugins
Triggersyespublish/subscribe channels provide some trigger functionalitynoyes 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)noneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationonline/offline synchronization between client and serveryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonospark-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 ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of command blocks and scriptsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes
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.yesyesnoyes
User concepts infoAccess controlyesPassword-based authenticationyesyes
More information provided by the system vendor
Apache IoTDBDragonflyObjectBoxSolr
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