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DBMS > Apache Phoenix vs. Blueflood vs. Netezza

System Properties Comparison Apache Phoenix vs. Blueflood vs. Netezza

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBlueflood  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseScalable TimeSeries DBMS based on CassandraData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitephoenix.apache.orgblueflood.iowww.ibm.com/­products/­netezza
Technical documentationphoenix.apache.orggithub.com/­rax-maas/­blueflood/­wiki
DeveloperApache Software FoundationRackspaceIBM
Initial release201420132000
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinux
Unix
Windows
Linux
OS X
Linux infoincluded in appliance
Data schemeyes infolate-bound, schema-on-read capabilitiespredefined schemeyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLyesnoyes
APIs and other access methodsJDBCHTTP RESTJDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoUsers with fine-grained authorization concept

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More resources
Apache PhoenixBluefloodNetezza infoAlso called PureData System for Analytics by IBM
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
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Bridge the SQL-NoSQL gap with Apache Phoenix
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11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime | Amazon Web Services
21 August 2019, AWS Blog

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