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DBMS > Apache Phoenix vs. CouchDB vs. Google Cloud Datastore vs. PouchDB

System Properties Comparison Apache Phoenix vs. CouchDB vs. Google Cloud Datastore vs. PouchDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSDocument storeDocument storeDocument store
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score9.30
Rank#45  Overall
#7  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score2.28
Rank#115  Overall
#21  Document stores
Websitephoenix.apache.orgcouchdb.apache.orgcloud.google.com/­datastorepouchdb.com
Technical documentationphoenix.apache.orgdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docspouchdb.com/­guides
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleApache Software Foundation
Initial release2014200520082012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.3.3, December 20237.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangJavaScript
Server operating systemsLinux
Unix
Windows
Android
BSD
Linux
OS X
Solaris
Windows
hostedserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyes, details hereno
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.nononono
Secondary indexesyesyes infovia viewsyesyes infovia views
SQL infoSupport of SQLyesnoSQL-like query language (GQL)no
APIs and other access methodsJDBCRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresuser defined functionsView functions in JavaScriptusing Google App EngineView functions in JavaScript
TriggersnoyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0ShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Multi-source replication using PaxosMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a single document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Apache PhoenixCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastorePouchDB
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