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DBMS > Apache IoTDB vs. Solr vs. TypeDB vs. Yanza

System Properties Comparison Apache IoTDB vs. Solr vs. TypeDB vs. Yanza

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonSolr  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it 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 FlinkA widely used distributed, scalable search engine based on Apache LuceneTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query languageTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSSearch engineGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Time Series DBMS
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
Score0.70
Rank#230  Overall
#20  Graph DBMS
#106  Relational DBMS
Websiteiotdb.apache.orgsolr.apache.orgtypedb.comyanza.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsolr.apache.org/­resources.htmltypedb.com/­docs
DeveloperApache Software FoundationApache Software FoundationVaticleYanza
Initial release2018200620162015
Current release1.1.0, April 20239.6.1, May 20242.26.3, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoGPL Version 3, commercial licenses availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
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
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesno
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.noyesnono
Secondary indexesyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like query languageSolr Parallel SQL Interfacenono
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP/JSON API
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
HTTP API
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
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresyesJava pluginsnono
Triggersyesyes infoUser configurable commands triggered on index changesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoby using Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication infoby using Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infoby using Apache Kafka and Apache Zookeeperno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infosubstituted by the relationship featureno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACIDno
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.yesyesno
User concepts infoAccess controlyesyesyes infoat REST API level; other APIs in progressno
More information provided by the system vendor
Apache IoTDBSolrTypeDB infoformerly named GraknYanza
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Apache IoTDBSolrTypeDB infoformerly named GraknYanza
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