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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonObjectBox  Xexclude from comparisonSolr  Xexclude from comparisonYottaDB  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 FlinkLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsA widely used distributed, scalable search engine based on Apache LuceneA fast and solid embedded Key-value store
Primary database modelTime Series DBMSObject oriented DBMS
Vector DBMS
Search engineKey-value store
Secondary database modelsTime Series DBMSSpatial DBMSRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
#7  Vector DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.28
Rank#306  Overall
#44  Key-value stores
Websiteiotdb.apache.orggithub.com/­objectbox
objectbox.io
solr.apache.orgyottadb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.objectbox.iosolr.apache.org/­resources.htmlyottadb.com/­resources/­documentation
DeveloperApache Software FoundationObjectBox LimitedApache Software FoundationYottaDB, LLC
Initial release2018201720062001
Current release1.1.0, April 20234.0 (May 2024)9.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Bindings are released under Apache 2.0 infoApache License 2.0Open Source infoApache Version 2Open Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Docker
Linux
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyes, plus "flex" map-like typesyes infosupports customizable data types and automatic typingno
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 indexesyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languagenoSolr Parallel SQL Interfaceby using the Octo plugin
APIs and other access methodsJDBC
Native API
Proprietary native APIJava API
RESTful HTTP/JSON API
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyesnoJava plugins
Triggersyesnoyes 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 replicasData sync between devices allowing occasional connected databases to work completely offlineyesyes
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
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnoyesyes
User concepts infoAccess controlyesyesyesUsers and groups based on OS-security mechanisms
More information provided by the system vendor
Apache IoTDBObjectBoxSolrYottaDB
News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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More resources
Apache IoTDBObjectBoxSolrYottaDB
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