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DBMS > Apache Phoenix vs. Google Cloud Bigtable vs. MonetDB vs. Riak TS

System Properties Comparison Apache Phoenix vs. Google Cloud Bigtable vs. MonetDB vs. Riak TS

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMonetDB  Xexclude from comparisonRiak TS  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.A relational database management system that stores data in columnsRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSTime Series 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
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Websitephoenix.apache.orgcloud.google.com/­bigtablewww.monetdb.org
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docswww.monetdb.org/­Documentationwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software FoundationGoogleMonetDB BVOpen Source, formerly Basho Technologies
Initial release2014201520042015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019Dec2023 (11.49), December 20233.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMozilla Public License 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCErlang
Server operating systemsLinux
Unix
Windows
hostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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 extensionsyes, limited
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
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++
Go
Java
JavaScript (Node.js)
Python
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 functionsnoyes, in SQL, C, RErlang
Triggersnonoyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding via remote tablesSharding
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 zonesnone 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 (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDno
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.yesno
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)fine grained access rights according to SQL-standardno

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Apache PhoenixGoogle Cloud BigtableMonetDBRiak TS
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