DBMS > Amazon DynamoDB vs. Hypertable vs. RDFox vs. Riak KV

System Properties Comparison Amazon DynamoDB vs. Hypertable vs. RDFox vs. Riak KV

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

High performance knowledge graph and semantic reasoning engine

Distributed, fault tolerant key-value store

Primary database model

Document store
Key-value store

Wide column store

Graph DBMS
RDF store

Key-value store

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

Secondary database models

Relational DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

aws.amazon.com/dynamodb

www.oxfordsemantic.tech

Technical documentation

docs.aws.amazon.com/dynamodb

docs.oxfordsemantic.tech

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

Developer

Amazon

Hypertable Inc.

Oxford Semantic Technologies

OpenSource, formerly Basho Technologies

Initial release

2012

2009

2017

2009

Current release

0.9.8.11, March 2016

6.0, Septermber 2022

3.2.0, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS
Windows

Linux
OS X

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

restricted

only exact value or prefix value scans

restricted

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

C++ API
Thrift

RESTful HTTP API
SPARQL 1.1

HTTP API
Native Erlang Interface

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

C
Java

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

Server-side scripts

Stored procedures

Erlang

Triggers

yes

by integration with AWS Lambda

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

replication via a shared file system

selectable replication factor

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

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

User concepts

Access control

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

Roles, resources, and access types

yes, using Riak Security

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