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DBMS > Apache IoTDB vs. H2 vs. InterSystems Caché vs. RDFox vs. Solr

System Properties Comparison Apache IoTDB vs. H2 vs. InterSystems Caché vs. RDFox vs. Solr

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonH2  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonRDFox  Xexclude from comparisonSolr  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed 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 FlinkFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A multi-model DBMS and application serverHigh performance knowledge graph and semantic reasoning engineA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Graph DBMS
RDF store
Search engine
Secondary database modelsSpatial DBMSDocument storeRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score42.91
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgwww.h2database.comwww.intersystems.com/­products/­cachewww.oxfordsemantic.techsolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.h2database.com/­html/­main.htmldocs.intersystems.comdocs.oxfordsemantic.techsolr.apache.org/­resources.html
DeveloperApache Software FoundationThomas MuellerInterSystemsOxford Semantic TechnologiesApache Software Foundation
Initial release20182005199720172006
Current release1.1.0, April 20232.2.220, July 20232018.1.4, May 20206.0, Septermber 20229.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesdepending on used data modelyes infoRDF schemasyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyesyes 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.nonoyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageyesyesnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
JDBC
ODBC
.NET Client API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
JavaC#
C++
Java
C
Java
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesJava Stored Procedures and User-Defined FunctionsyesJava plugins
Triggersyesyesyesyes 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)nonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasWith clustering: 2 database servers on different computers operate on identical copies of a databaseSource-replica replicationreplication via a shared file systemyes
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
Immediate ConsistencyImmediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsEventual Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess rights for users, groups and rolesRoles, resources, and access typesyes

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More resources
Apache IoTDBH2InterSystems CachéRDFoxSolr
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