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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonH2  Xexclude from comparisonSolr  Xexclude from comparisonTDengine  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.A widely used distributed, scalable search engine based on Apache LuceneTime Series DBMS and big data platform
Primary database modelTime Series DBMSRelational DBMSSearch engineTime Series DBMS
Secondary database modelsSpatial DBMSSpatial DBMSRelational 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
Score42.91
Rank#24  Overall
#3  Search engines
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteiotdb.apache.orgwww.h2database.comsolr.apache.orggithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.h2database.com/­html/­main.htmlsolr.apache.org/­resources.htmldocs.tdengine.com
DeveloperApache Software FoundationThomas MuellerApache Software FoundationTDEngine, previously Taos Data
Initial release2018200520062019
Current release1.1.0, April 20232.2.220, July 20239.6.0, April 20243.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache Version 2Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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 languageyesSolr Parallel SQL InterfaceStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
Native API
JDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyesJava Stored Procedures and User-Defined FunctionsJava pluginsno
Triggersyesyesyes infoUser configurable commands triggered on index changesyes, via alarm monitoring
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 databaseyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknospark-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 Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic 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-standardyesyes
More information provided by the system vendor
Apache IoTDBH2SolrTDengine
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
Apache IoTDBH2SolrTDengine
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