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DBMS > Apache Druid vs. Apache Phoenix vs. Dragonfly vs. Netezza

System Properties Comparison Apache Druid vs. Apache Phoenix vs. Dragonfly vs. Netezza

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDragonfly  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA scale-out RDBMS with evolutionary schema built on Apache HBaseA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value storeRelational DBMS
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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitedruid.apache.orgphoenix.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.ibm.com/­products/­netezza
Technical documentationdruid.apache.org/­docs/­latest/­designphoenix.apache.orgwww.dragonflydb.io/­docs
DeveloperApache Software Foundation and contributorsApache Software FoundationDragonflyDB team and community contributorsIBM
Initial release2012201420232000
Current release29.0.1, April 20245.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0, March 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoBSL 1.1commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinux
OS X
Unix
Linux
Unix
Windows
LinuxLinux infoincluded in appliance
Data schemeyes infoschema-less columns are supportedyes infolate-bound, schema-on-read capabilitiesscheme-freeyes
Typing infopredefined data types such as float or dateyesyesstrings, hashes, lists, sets, sorted sets, bit arraysyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingyesnoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCProprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
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
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnouser defined functionsLuayes
Triggersnonopublish/subscribe channels provide some trigger functionalityno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic execution of command blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, strict serializability by the serveryes
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.noyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPassword-based authenticationUsers with fine-grained authorization concept

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More resources
Apache DruidApache PhoenixDragonflyNetezza infoAlso called PureData System for Analytics by IBM
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