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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  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.Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSRelational 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­bigtablewww.hawkular.orgwww.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 Hat
Initial release2014201520142014 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 2.0Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Windows
Linux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesnonoyes
SQL infoSupport of SQLyesnonoyes infodistributed, parallel query execution
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTADO.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
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonouser defined functions
Triggersnonoyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on Cassandrahorizontal 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 Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnono
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 integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID infoMVCC
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.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)nofine grained access rights according to SQL-standard

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More resources
Apache PhoenixGoogle Cloud BigtableHawkular MetricsPostgres-XL
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