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DBMS > Apache IoTDB vs. Kdb vs. Solr vs. TimesTen

System Properties Comparison Apache IoTDB vs. Kdb vs. Solr vs. TimesTen

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonKdb  Xexclude from comparisonSolr  Xexclude from comparisonTimesTen  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 FlinkHigh performance Time Series DBMSA widely used distributed, scalable search engine based on Apache LuceneIn-Memory RDBMS compatible to Oracle
Primary database modelTime Series DBMSTime Series DBMS
Vector DBMS
Search engineRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score7.70
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Score1.35
Rank#165  Overall
#75  Relational DBMS
Websiteiotdb.apache.orgkx.comsolr.apache.orgwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcode.kx.comsolr.apache.org/­resources.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software FoundationKx Systems, a division of First Derivatives plcApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20182000 infokdb was released 2000, kdb+ in 200320061998
Current release1.1.0, April 20233.6, May 20189.5.0, February 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree 32-bit versionOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaqJava
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.noyesyesno
Secondary indexesyesyes infotable attribute 'grouped'yes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (q)Solr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
Native API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesuser defined functionsJava pluginsPL/SQL
Triggersyesyes infowith viewsyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkno infosimilar paradigm used for internal processingspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlyesrights management via user accountsyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBKdbSolrTimesTen
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Apache IoTDBKdbSolrTimesTen
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