DBMS > Apache Phoenix vs. FatDB vs. Postgres-XL vs. PouchDB

System Properties Comparison Apache Phoenix vs. FatDB vs. Postgres-XL vs. PouchDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

phoenix.apache.org

www.postgres-xl.org

pouchdb.com

Technical documentation

phoenix.apache.org

www.postgres-xl.org/documentation

pouchdb.com/guides

Developer

Apache Software Foundation

FatCloud

Apache Software Foundation

Initial release

2014

2012

2014

since 2012, originally named StormDB

2012

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

10 R1, October 2018

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Mozilla public license

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Server operating systems

Linux
Unix
Windows

Windows

Linux
macOS

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

via views

SQL

Support of SQL

yes

Via inetgration in SQL Server

yes

distributed, parallel query execution

APIs and other access methods

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

via applications

user defined functions

View functions in JavaScript

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

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

Amazon EMR 4.7.0 – Apache Tez & Phoenix, Updates to Existing Apps | Amazon Web Services
2 June 2016, AWS Blog

provided by Google News

Building an Offline First App with PouchDB — SitePoint
10 March 2014, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database — SitePoint
7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, ibm.com

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
7 March 2017, SitePoint

Offline-first web and mobile apps: Top frameworks and components
22 January 2019, TechBeacon

provided by Google News

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