DBMS > NSDb vs. RDFox vs. RocksDB

System Properties Comparison NSDb vs. RDFox vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

High performance knowledge graph and semantic reasoning engine

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

Primary database model

Time Series DBMS

Graph DBMS
RDF store

Key-value store

Secondary database models

Relational DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

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

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

Website

nsdb.io

www.oxfordsemantic.tech

rocksdb.org

Technical documentation

nsdb.io/Architecture

docs.oxfordsemantic.tech

github.com/facebook/rocksdb/wiki

Developer

Oxford Semantic Technologies

Facebook, Inc.

Initial release

2017

2013

Current release

6.0, Septermber 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Scala

C++

Server operating systems

Linux
macOS

Linux
macOS
Windows

Linux

Data scheme

yes

RDF schemas

schema-free

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

APIs and other access methods

gRPC
HTTP REST
WebSocket

RESTful HTTP API
SPARQL 1.1

C++ API
Java API

Supported programming languages

Java
Scala

C
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Using Apache Lucene

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

Roles, resources, and access types

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