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DBMS > Apache IoTDB vs. H2 vs. Riak KV vs. Solr

System Properties Comparison Apache IoTDB vs. H2 vs. Riak KV vs. Solr

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonH2  Xexclude from comparisonRiak KV  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 FlinkFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Distributed, fault tolerant key-value storeA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engine
Secondary database modelsSpatial 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
Score4.10
Rank#82  Overall
#9  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgwww.h2database.comsolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.h2database.com/­html/­main.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latestsolr.apache.org/­resources.html
DeveloperApache Software FoundationThomas MuellerOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2018200520092006
Current release1.1.0, April 20232.2.220, July 20233.2.0, December 20229.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache version 2, commercial enterprise editionOpen 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 languageJavaJavaErlangJava
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesnoyes 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 indexesyesyesrestrictedyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageyesnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
JDBC
ODBC
HTTP API
Native Erlang Interface
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
JavaC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.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 FunctionsErlangJava plugins
Triggersyesyesyes infopre-commit hooks and post-commit hooksyes 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 infono "single point of failure"Sharding
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 databaseselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesspark-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 ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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 controlyesfine grained access rights according to SQL-standardyes, using Riak Securityyes

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More resources
Apache IoTDBH2Riak KVSolr
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