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DBMS > Apache IoTDB vs. Citus vs. Elasticsearch vs. Hive vs. MonetDB

System Properties Comparison Apache IoTDB vs. Citus vs. Elasticsearch vs. Hive vs. MonetDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonElasticsearch  Xexclude from comparisonHive  Xexclude from comparisonMonetDB  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 FlinkScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricdata warehouse software for querying and managing large distributed datasets, built on HadoopA relational database management system that stores data in columns
Primary database modelTime Series DBMSRelational DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Websiteiotdb.apache.orgwww.citusdata.comwww.elastic.co/­elasticsearchhive.apache.orgwww.monetdb.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homewww.monetdb.org/­Documentation
DeveloperApache Software FoundationElasticApache Software Foundation infoinitially developed by FacebookMonetDB BV
Initial release20182010201020122004
Current release1.1.0, April 20238.1, December 20188.6, January 20233.1.3, April 2022Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availableOpen Source infoElastic LicenseOpen Source infoApache Version 2Open Source infoMozilla Public License 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCJavaJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAll OS with a Java VMAll OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionsSQL-like query languageSQL-like DML and DDL statementsyes infoSQL 2003 with some extensions
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yesyes infouser defined functions and integration of map-reduceyes, in SQL, C, R
Triggersyesyesyes infoby using the 'percolation' featurenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardingSharding via remote tables
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 replication infoother methods possible by using 3rd party extensionsyesselectable replication factornone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoES-Hadoop Connectoryes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnoMemcached and Redis integration
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess rights for users, groups and rolesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBCitusElasticsearchHiveMonetDB
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