DBMS > Amazon SimpleDB vs. Oracle Berkeley DB vs. Oracle NoSQL vs. STSdb vs. WakandaDB

System Properties Comparison Amazon SimpleDB vs. Oracle Berkeley DB vs. Oracle NoSQL vs. STSdb vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Widely used in-process key-value store

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Key-value store
Relational DBMS

Key-value store

Object oriented DBMS

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

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

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

aws.amazon.com/simpledb

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

www.oracle.com/database/nosql/technologies/nosql

github.com/STSSoft/STSdb4

wakanda.github.io

Technical documentation

docs.aws.amazon.com/simpledb

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

wakanda.github.io/doc

Developer

Amazon

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle

STS Soft SC

Wakanda SAS

Initial release

2007

1994

2011

2012

Current release

18.1.40, May 2020

23.3, December 2023

4.0.8, September 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPLv2, commercial license available

Open Source

AGPLv3, extended 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)

Java

C++, JavaScript

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
Solaris SPARC/x86

Windows

Linux
OS X
Windows

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

optional

yes

primitive types and user defined types (classes)

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

only with the Berkeley DB XML edition

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

.NET Client API

RESTful HTTP API

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

.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

C
C#
Go
Java
JavaScript (Node.js)
Python

C#
Java

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrent data updates can be detected by the application

ACID

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles

yes

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More resources

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