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DBMS > Apache Phoenix vs. Google BigQuery vs. MySQL vs. Netezza

System Properties Comparison Apache Phoenix vs. Google BigQuery vs. MySQL vs. Netezza

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonMySQL  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseLarge scale data warehouse service with append-only tablesWidely used open source RDBMSData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSRelational DBMSRelational DBMS infoKey/Value like access via memcached APIRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score1083.74
Rank#2  Overall
#2  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­bigquerywww.mysql.comwww.ibm.com/­products/­netezza
Technical documentationphoenix.apache.orgcloud.google.com/­bigquery/­docsdev.mysql.com/­doc
DeveloperApache Software FoundationGoogleOracle infosince 2010, originally MySQL AB, then SunIBM
Initial release2014201019952000
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.4.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++
Server operating systemsLinux
Unix
Windows
hostedFreeBSD
Linux
OS X
Solaris
Windows
Linux infoincluded in appliance
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
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
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesyesyes infowith proprietary extensionsyes
APIs and other access methodsJDBCRESTful HTTP/JSON APIADO.NET
JDBC
ODBC
Proprietary native API
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functionsuser defined functions infoin JavaScriptyes infoproprietary syntaxyes
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning, sharding with MySQL Cluster or MySQL FabricSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataACID infonot for MyISAM storage engineACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Users with fine-grained authorization concept infono user groups or rolesUsers with fine-grained authorization concept

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More resources
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