DBMS > Amazon DynamoDB vs. RDF4J vs. Sphinx vs. VoltDB

System Properties Comparison Amazon DynamoDB vs. RDF4J vs. Sphinx vs. VoltDB

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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

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

Open source search engine for searching in data from different sources, e.g. relational databases

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Key-value store

RDF store

Search engine

Relational DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

aws.amazon.com/dynamodb

rdf4j.org

sphinxsearch.com

www.voltdb.com

Technical documentation

docs.aws.amazon.com/dynamodb

rdf4j.org/documentation

sphinxsearch.com/docs

docs.voltdb.com

Developer

Amazon

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

Sphinx Technologies Inc.

VoltDB Inc.

Initial release

2012

2004

2001

2010

Current release

3.5.1, February 2023

11.3, April 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL version 2, commercial licence available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java, C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
PHP
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

The original contents of fields are not stored in the Sphinx index.

yes

Snapshots and command logging

User concepts

Access control

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

Users and roles with access to stored procedures

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