DBMS > RDF4J vs. RocksDB vs. Rockset

System Properties Comparison RDF4J vs. RocksDB vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

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)

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

RDF store

Key-value store

Document store

Secondary database models

Relational DBMS
Search engine

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

rdf4j.org

rocksdb.org

rockset.com

Technical documentation

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

docs.rockset.com

Developer

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

Facebook, Inc.

Rockset

Initial release

2004

2013

2019

Current release

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix
Windows

Linux

hosted

Data scheme

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

Read-only SQL queries, including JOINs

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

HTTP REST

Supported programming languages

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Access rights for users and organizations can be defined via Rockset console

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