DBMS > Amazon DocumentDB vs. Infobright vs. Oracle Berkeley DB vs. PouchDB vs. STSdb

System Properties Comparison Amazon DocumentDB vs. Infobright vs. Oracle Berkeley DB vs. PouchDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Widely used in-process key-value store

JavaScript DBMS with an API inspired by CouchDB

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Key-value store

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

aws.amazon.com/documentdb

ignitetech.com/softwarelibrary/infobrightdb

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

pouchdb.com

github.com/STSSoft/STSdb4

Technical documentation

aws.amazon.com/documentdb/resources

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

pouchdb.com/guides

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Apache Software Foundation

STS Soft SC

Initial release

2019

2005

1994

2012

2011

Current release

18.1.40, May 2020

7.1.1, June 2019

4.0.8, September 2015

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

commercial license available

Open Source

GPLv2, commercial license available

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

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

JavaScript

Server operating systems

hosted

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

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

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Knowledge Grid Technology used instead

yes

via views

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

.NET Client API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.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

C#
Java

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Source-replica replication

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

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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 rights for users and roles

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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