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DBMS > Apache Druid vs. Citus vs. Hive vs. Ignite

System Properties Comparison Apache Druid vs. Citus vs. Hive vs. Ignite

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCitus  Xexclude from comparisonHive  Xexclude from comparisonIgnite  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLdata warehouse software for querying and managing large distributed datasets, built on HadoopApache 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 modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSKey-value store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitedruid.apache.orgwww.citusdata.comhive.apache.orgignite.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.citusdata.comcwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docs
DeveloperApache Software Foundation and contributorsApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release2012201020122015
Current release29.0.1, April 20248.1, December 20183.1.3, April 2022Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoAGPL, commercial license also availableOpen Source infoApache Version 2Open 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 languageJavaCJavaC++, Java, .Net
Server operating systemsLinux
OS X
Unix
LinuxAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes
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.noyes infospecific XML type available, but no XML query functionalityyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyes infostandard, with numerous extensionsSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)
Triggersnoyesnoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replication infoother methods possible by using 3rd party extensionsselectable replication factoryes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights for users, groups and rolesSecurity Hooks for custom implementations

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Apache DruidCitusHiveIgnite
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