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DBMS > Apache IoTDB vs. Citus vs. Dragonfly vs. Hive vs. TinkerGraph

System Properties Comparison Apache IoTDB vs. Citus vs. Dragonfly vs. Hive vs. TinkerGraph

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonDragonfly  Xexclude from comparisonHive  Xexclude from comparisonTinkerGraph  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 drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instancedata warehouse software for querying and managing large distributed datasets, built on HadoopA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelTime Series DBMSRelational DBMSKey-value storeRelational DBMSGraph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websiteiotdb.apache.orgwww.citusdata.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
hive.apache.orgtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comwww.dragonflydb.io/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software FoundationDragonflyDB team and community contributorsApache Software Foundation infoinitially developed by Facebook
Initial release20182010202320122009
Current release1.1.0, April 20238.1, December 20181.0, March 20233.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availableOpen Source infoBSL 1.1Open Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++JavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxAll OS with a Java VM
Data schemeyesyesscheme-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesstrings, hashes, lists, sets, sorted sets, bit arraysyesyes
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 functionalitynono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionsnoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
Thrift
TinkerPop 3
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C++
Java
PHP
Python
Groovy
Java
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Luayes infouser defined functions and integration of map-reduceno
Triggersyesyespublish/subscribe channels provide some trigger functionalitynono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingnone
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 extensionsSource-replica replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual ConsistencyEventual Consistencynone
Foreign keys infoReferential integritynoyesnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic execution of command blocks and scriptsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes, strict serializability by the serveryesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardPassword-based authenticationAccess rights for users, groups and rolesno

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Apache IoTDBCitusDragonflyHiveTinkerGraph
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