DBMS > NSDb vs. RDFox vs. STSdb vs. TimesTen

System Properties Comparison NSDb vs. RDFox vs. STSdb vs. TimesTen

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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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

nsdb.io

www.oxfordsemantic.tech

github.com/STSSoft/STSdb4

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

nsdb.io/Architecture

docs.oxfordsemantic.tech

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Oxford Semantic Technologies

STS Soft SC

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2017

2011

1998

Current release

6.0, Septermber 2022

4.0.8, September 2015

Release 22.1

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Scala

C++

Server operating systems

Linux
macOS

Linux
macOS
Windows

Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

RDF schemas

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

yes

primitive types and user defined types (classes)

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

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

RESTful HTTP API
SPARQL 1.1

.NET Client API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

Java
Scala

C
Java

C#
Java

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

replication via a shared file system

none

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Using Apache Lucene

yes

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

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