DBMS > Fauna vs. HarperDB vs. Oracle Berkeley DB vs. PouchDB

System Properties Comparison Fauna vs. HarperDB vs. Oracle Berkeley DB vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Widely used in-process key-value store

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

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

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

fauna.com

www.harperdb.io

www.oracle.com/database/technologies/related/berkeleydb.html

pouchdb.com

Technical documentation

docs.fauna.com

docs.harperdb.io/docs

docs.oracle.com/cd/E17076_05/html/index.html

pouchdb.com/guides

Developer

Fauna, Inc.

HarperDB

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Apache Software Foundation

Initial release

2014

2017

1994

2012

Current release

3.1, August 2021

18.1.40, May 2020

7.1.1, June 2019

License

Commercial or Open Source

commercial

free community edition available

Open Source

commercial license available

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

Node.js

C, Java, C++ (depending on the Berkeley DB edition)

JavaScript

Server operating systems

hosted

Linux
OS X

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

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

Data scheme

schema-free

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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

only with the Berkeley DB XML edition

Secondary indexes

yes

via views

SQL

Support of SQL

SQL-like data manipulation statements

yes

SQL interfaced based on SQLite is available

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions

Custom Functions

since release 3.1

View functions in JavaScript

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

A table resides as a whole on one (or more) nodes in a cluster

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

the nodes on which a table resides can be defined

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Identity management, authentication, and access control

Access rights for users and roles

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