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DBMS > Apache IoTDB vs. Apache Phoenix vs. Heroic vs. Hive vs. Linter

System Properties Comparison Apache IoTDB vs. Apache Phoenix vs. Heroic vs. Hive vs. Linter

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonHeroic  Xexclude from comparisonHive  Xexclude from comparisonLinter  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 FlinkA scale-out RDBMS with evolutionary schema built on Apache HBaseTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchdata warehouse software for querying and managing large distributed datasets, built on HadoopRDBMS for high security requirements
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Websiteiotdb.apache.orgphoenix.apache.orggithub.com/­spotify/­heroichive.apache.orglinter.ru
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgspotify.github.io/­heroiccwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software FoundationApache Software FoundationSpotifyApache Software Foundation infoinitially developed by Facebookrelex.ru
Initial release20182014201420121990
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaJavaC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
All OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
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.nononono
Secondary indexesyesyesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
Native API
JDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Thrift
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresyesuser defined functionsnoyes infouser defined functions and integration of map-reduceyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
yesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkHadoop integrationnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
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.yesyesno
User concepts infoAccess controlyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and rolesfine grained access rights according to SQL-standard

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Apache IoTDBApache PhoenixHeroicHiveLinter
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