DBMS > RDF4J vs. RocksDB vs. TerminusDB vs. Transwarp Hippo

System Properties Comparison RDF4J vs. RocksDB vs. TerminusDB vs. Transwarp Hippo

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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)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Secondary database models

Document store
RDF store

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

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.05
Rank	#386	Overall
	#15	Vector DBMS

Website

rdf4j.org

rocksdb.org

terminusdb.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

terminusdb.github.io/terminusdb/#

Developer

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

Facebook, Inc.

DataChemist Ltd.

Initial release

2004

2013

2018

2023

Current release

9.2.1, May 2024

11.0.0, January 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Prolog, Rust

C++

Server operating systems

Linux
OS X
Unix
Windows

Linux

Linux
macOS

Data scheme

yes

RDF Schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

SQL-like query language (WOQL)

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

RESTful HTTP API

Supported programming languages

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

JavaScript
Python

C++
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

yes

ACID

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 journaling

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

Role-based access control

Role based access control and fine grained access rights

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