DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. DataFS vs. Postgres-XL

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. DataFS vs. Postgres-XL

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Editorial information provided by DB-Engines
Name	Apache Phoenix  Xexclude from comparison	Atos Standard Common Repository  Xexclude from comparison	DataFS  Xexclude from comparison	Postgres-XL  Xexclude from comparison
		This system has been discontinued and will be removed from the DB-Engines ranking.
Description	A scale-out RDBMS with evolutionary schema built on Apache HBase	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.	Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database model	Relational DBMS	Document store Key-value store	Object oriented DBMS	Relational DBMS
Secondary database models			Graph DBMS	Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 2.06 Rank #123   Overall #58   Relational DBMS		Score 0.09 Rank #360   Overall #17   Object oriented DBMS	Score 0.53 Rank #254   Overall #117   Relational DBMS
Website	phoenix.apache.org	atos.net/en/convergence-creators/portfolio/standard-common-repository	newdatabase.com	www.postgres-xl.org
Technical documentation	phoenix.apache.org		dev.mobiland.com/­Overview.xsp	www.postgres-xl.org/­documentation
Developer	Apache Software Foundation	Atos Convergence Creators	Mobiland AG
Initial release	2014	2016	2018	2014 since 2012, originally named StormDB
Current release	5.0-HBase2, July 2018 and 4.15-HBase1, December 2019	1703	1.1.263, October 2022	10 R1, October 2018
License Commercial or Open Source	Open Source Apache Version 2.0	commercial	commercial	Open Source Mozilla public license
Cloud-based only Only available as a cloud service	no	no	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	Java		C
Server operating systems	Linux Unix Windows	Linux	Windows	Linux macOS
Data scheme	yes late-bound, schema-on-read capabilities	Schema and schema-less with LDAP views	Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)	yes
Typing predefined data types such as float or date	yes	optional	yes	yes
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.	no	yes	no	yes XML type, but no XML query functionality
Secondary indexes	yes	yes	no	yes
SQL Support of SQL	yes	no	no	yes distributed, parallel query execution
APIs and other access methods	JDBC	LDAP	.NET Client API Proprietary client DLL WinRT client	ADO.NET JDBC native C library ODBC streaming API for large objects
Supported programming languages	C C# C++ Go Groovy Java PHP Python Scala	All languages with LDAP bindings	.Net C C# C++ VB.Net	.Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl
Server-side scripts Stored procedures	user defined functions	no		user defined functions
Triggers	no	yes	no, except callback-events from server when changes happened	yes
Partitioning methods Methods for storing different data on different nodes	Sharding	Sharding cell division	Proprietary Sharding system	horizontal partitioning
Replication methods Methods for redundantly storing data on multiple nodes	Multi-source replication Source-replica replication	yes
MapReduce Offers an API for user-defined Map/Reduce methods	Hadoop integration		no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Immediate Consistency
Foreign keys Referential integrity	no	no	yes	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	ACID	Atomic execution of specific operations	ACID	ACID MVCC
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	yes	no	no
User concepts Access control	Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy	LDAP bind authentication	Windows-Profile	fine grained access rights according to SQL-standard
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More resources
	Apache Phoenix	Atos Standard Common Repository	DataFS	Postgres-XL
DB-Engines blog posts	Cloudera's HBase PaaS offering now supports Complex Transactions 11 August 2021,  Krishna Maheshwari (sponsor)  show all
Recent citations in the news	Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services 2 June 2016, AWS Blog Azure #HDInsight Apache Phoenix now supports Zeppelin 16 August 2018, Microsoft Bridge the SQL-NoSQL gap with Apache Phoenix 4 February 2016, InfoWorld Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated 27 March 2017, SDTimes.com Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0 18 April 2019, eWeek provided by Google News

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