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DBMS > Apache Phoenix vs. Google Cloud Bigtable vs. Hawkular Metrics vs. Netezza vs. Postgres-XL

System Properties Comparison Apache Phoenix vs. Google Cloud Bigtable vs. Hawkular Metrics vs. Netezza vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Data warehouse and analytics appliance part of IBM PureSystemsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­bigtablewww.hawkular.orgwww.ibm.com/­products/­netezzawww.postgres-xl.org
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.postgres-xl.org/­documentation
DeveloperApache Software FoundationGoogleCommunity supported by Red HatIBM
Initial release20142015201420002014 infosince 2012, originally named StormDB
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201910 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Windows
Linux infoincluded in applianceLinux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nononoyes infoXML type, but no XML query functionality
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLyesnonoyesyes infodistributed, parallel query execution
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTJDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonoyesuser defined functions
Triggersnonoyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on CassandraSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Apache PhoenixGoogle Cloud BigtableHawkular MetricsNetezza infoAlso called PureData System for Analytics by IBMPostgres-XL
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