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DBMS > Apache IoTDB vs. Apache Phoenix vs. Citus vs. Ignite

System Properties Comparison Apache IoTDB vs. Apache Phoenix vs. Citus vs. Ignite

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonCitus  Xexclude from comparisonIgnite  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 HBaseScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelTime Series DBMSRelational DBMSRelational DBMSKey-value store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websiteiotdb.apache.orgphoenix.apache.orgwww.citusdata.comignite.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgdocs.citusdata.comapacheignite.readme.io/­docs
DeveloperApache Software FoundationApache Software FoundationApache Software Foundation
Initial release2018201420102015
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20198.1, December 2018Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoAGPL, commercial license also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCC++, Java, .Net
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes infospecific XML type available, but no XML query functionalityyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyesyes infostandard, with numerous extensionsANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
Native API
JDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes (compute grid and cache interceptors can be used instead)
Triggersyesnoyesyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
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
Source-replica replication infoother methods possible by using 3rd party extensionsyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkHadoop integrationnoyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesnoyes
User concepts infoAccess controlyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardSecurity Hooks for custom implementations

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Apache IoTDBApache PhoenixCitusIgnite
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