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DBMS > Hawkular Metrics vs. HBase vs. Hive vs. Vitess

System Properties Comparison Hawkular Metrics vs. HBase vs. Hive vs. Vitess

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Wide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.hawkular.orghbase.apache.orghive.apache.orgvitess.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homevitess.io/­docs
DeveloperCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookThe Linux Foundation, PlanetScale
Initial release2014200820122013
Current release2.3.4, January 20213.1.3, April 202215.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoApache Version 2Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaGo
Server operating systemsLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
All OS with a Java VMDocker
Linux
macOS
Data schemeschema-freeschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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 indexesnonoyesyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes infowith proprietary extensions
APIs and other access methodsHTTP RESTJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesGo
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceyes infoproprietary syntax
Triggersyes infovia Hawkular Alertingyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)noACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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 controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and rolesUsers with fine-grained authorization concept infono user groups or roles

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More resources
Hawkular MetricsHBaseHiveVitess
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