DBMS > Apache Phoenix vs. FoundationDB vs. PouchDB vs. SQLite

System Properties Comparison Apache Phoenix vs. FoundationDB vs. PouchDB vs. SQLite

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

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

Ordered key-value store. Core features are complimented by layers.

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Document store

Relational DBMS

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

phoenix.apache.org

github.com/apple/foundationdb

pouchdb.com

www.sqlite.org

Technical documentation

phoenix.apache.org

apple.github.io/foundationdb

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

Apache Software Foundation

FoundationDB

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2014

2013

2012

2000

Current release

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

6.2.28, November 2020

7.1.1, June 2019

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C++

JavaScript

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

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

server-less

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

some layers support schemas

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

some layers support typing

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

supported in specific SQL layer only

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

in SQL-layer only

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

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

Linearizable consistency

Eventual Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

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

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