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DBMS > Amazon SimpleDB vs. EXASOL vs. RDF4J vs. Riak KV vs. SQL.JS

System Properties Comparison Amazon SimpleDB vs. EXASOL vs. RDF4J vs. Riak KV vs. SQL.JS

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Distributed, fault tolerant key-value store

Port of SQLite to JavaScript

Primary database model

Key-value store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	1.89
Rank	#128	Overall
	#22	Key-value stores

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	0.53
Rank	#246	Overall
	#115	Relational DBMS

Website

aws.amazon.com/simpledb

Technical documentation

docs.aws.amazon.com/simpledb

www.exasol.com/resources

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

sql.js.org/documentation/index.html

Developer

Amazon

Exasol

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

OpenSource, formerly Basho Technologies

Alon Zakai

enhancements implemented by others

Initial release

2007

2000

2004

2009

2012

Current release

3.2.0, December 2022

License

Commercial or Open Source

commercial

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache version 2, commercial enterprise edition

Open Source

Cloud-based only

Only available as a cloud service

yes

no

no

no

no

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

JavaScript

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux
OS X

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

Data scheme

schema-free

yes

yes

RDF Schemas

schema-free

yes

Typing

predefined data types such as float or date

no

yes

yes

no

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.

no

no

no

Secondary indexes

yes

All columns are indexed automatically

yes

yes

restricted

SQL

Support of SQL

no

yes

no

no

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

JavaScript API

Supported programming languages

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

Java
Lua
Python
R

Java
PHP
Python

C

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript

Server-side scripts

Stored procedures

no

user defined functions

yes

Erlang

no

Triggers

no

yes

yes

yes

pre-commit hooks and post-commit hooks

no

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

none

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

no

yes

Hadoop integration

no

yes

no

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

no

yes

no

links between data sets can be stored

yes

Transaction concepts

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

no

Concurrent data updates can be detected by the application

ACID

ACID

Isolation support depends on the API used

no

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

yes

Durability

Support for making data persistent

yes

yes

yes

in-memory storage is supported as well

yes

no

except by serializing a db to a file

In-memory capabilities

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

yes

yes

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, groups and roles according to SQL-standard

no

yes, using Riak Security

no

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More resources

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