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DBMS > Apache Phoenix vs. HBase vs. MonetDB vs. Riak KV

System Properties Comparison Apache Phoenix vs. HBase vs. MonetDB vs. Riak KV

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHBase  Xexclude from comparisonMonetDB  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseWide-column store based on Apache Hadoop and on concepts of BigTableA relational database management system that stores data in columnsDistributed, fault tolerant key-value store
Primary database modelRelational DBMSWide column storeRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitephoenix.apache.orghbase.apache.orgwww.monetdb.org
Technical documentationphoenix.apache.orghbase.apache.org/­book.htmlwww.monetdb.org/­Documentationwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by PowersetMonetDB BVOpenSource, formerly Basho Technologies
Initial release2014200820042009
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.3.4, January 2021Dec2023 (11.49), December 20233.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoMozilla Public License 2.0Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCErlang
Server operating systemsLinux
Unix
Windows
Linux
Unix
Windows infousing Cygwin
FreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesno
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.nonono
Secondary indexesyesnoyesrestricted
SQL infoSupport of SQLyesnoyes infoSQL 2003 with some extensionsno
APIs and other access methodsJDBCJava API
RESTful HTTP API
Thrift
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
HTTP API
Native Erlang Interface
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsyes infoCoprocessors in Javayes, in SQL, C, RErlang
Triggersnoyesyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding via remote tablesSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
none infoSource-replica replication available in experimental statusselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDno
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.yesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standardyes, using Riak Security

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Apache PhoenixHBaseMonetDBRiak KV
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