DBMS > Amazon CloudSearch vs. RDF4J vs. RocksDB

System Properties Comparison Amazon CloudSearch vs. RDF4J vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

A hosted search engine 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.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Search engine

RDF store

Key-value store

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

Score	1.87
Rank	#140	Overall
	#12	Search engines

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

aws.amazon.com/cloudsearch

rdf4j.org

rocksdb.org

Technical documentation

docs.aws.amazon.com/cloudsearch

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Amazon

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

Facebook, Inc.

Initial release

2012

2004

2013

Current release

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

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

Linux
OS X
Unix
Windows

Linux

Data scheme

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

all search fields are automatically indexed

yes

SQL

Support of SQL

APIs and other access methods

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

Supported programming languages

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Foreign keys

Referential integrity

Transaction concepts

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

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

authentication via encrypted signatures

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