DBMS > Amazon DynamoDB vs. mSQL vs. RDF4J vs. Speedb

System Properties Comparison Amazon DynamoDB vs. mSQL vs. RDF4J vs. Speedb

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB

Primary database model

Document store
Key-value store

Relational DBMS

RDF store

Key-value store

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.20
Rank	#310	Overall
	#44	Key-value stores

Website

aws.amazon.com/dynamodb

hughestech.com.au/products/msql

rdf4j.org

www.speedb.io

Technical documentation

docs.aws.amazon.com/dynamodb

rdf4j.org/documentation

Developer

Amazon

Hughes Technologies

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

Speedb

Initial release

2012

1994

2004

2020

Current release

4.4, October 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free licenses can be provided

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0; 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

Java

C++

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Unix
Windows

Linux
Windows

Data scheme

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Isolation support depends on the API used

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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 can be defined via the AWS Identity and Access Management (IAM)

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