DBMS > Newts vs. RDF4J vs. Vertica vs. YottaDB

System Properties Comparison Newts vs. RDF4J vs. Vertica vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS based on Cassandra

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

A fast and solid embedded Key-value store

Primary database model

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

Relational DBMS

using the Octo plugin

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

opennms.github.io/newts

rdf4j.org

www.vertica.com

yottadb.com

Technical documentation

github.com/OpenNMS/newts/wiki

rdf4j.org/documentation

vertica.com/documentation

yottadb.com/resources/documentation

Developer

OpenNMS Group

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

OpenText

previously Micro Focus and Hewlett Packard

YottaDB, LLC

Initial release

2014

2004

2005

2001

Current release

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Limited community edition free

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux

Docker
Linux

Data scheme

schema-free

yes

RDF Schemas

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

by using the Octo plugin

APIs and other access methods

HTTP REST
Java API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Java

Java
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

ACID

optimistic locking

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

Users and groups based on OS-security mechanisms

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