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DBMS > Apache IoTDB vs. H2 vs. Hypertable vs. Solr

System Properties Comparison Apache IoTDB vs. H2 vs. Hypertable vs. Solr

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonH2  Xexclude from comparisonHypertable  Xexclude from comparisonSolr  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and 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.An open source BigTable implementation based on distributed file systems such as HadoopA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSRelational DBMSWide column storeSearch engine
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score8.22
Rank#50  Overall
#32  Relational DBMS
Score44.28
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.htmlsolr.apache.org/­resources.html
DeveloperApache Software FoundationThomas MuellerHypertable Inc.Apache Software Foundation
Initial release2018200520092006
Current release1.1.0, April 20232.2.220, July 20230.9.8.11, March 20169.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoGNU version 3. Commercial license availableOpen 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 languageJavaJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
OS X
Windows infoan inofficial Windows port is available
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.nonoyes
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyes 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
C++ API
Thrift
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
JavaC++
Java
Perl
PHP
Python
Ruby
.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 FunctionsnoJava plugins
Triggersyesyesnoyes 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)noneShardingSharding
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 factor on file system levelyes
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 ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
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-standardnoyes

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Apache IoTDBH2HypertableSolr
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