DBMS > DuckDB vs. Linter vs. RDF4J vs. Yaacomo

System Properties Comparison DuckDB vs. Linter vs. RDF4J vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

RDBMS for high security requirements

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

RDF store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	5.61
Rank	#60	Overall
	#34	Relational DBMS

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

duckdb.org

linter.ru

rdf4j.org

yaacomo.com

Technical documentation

duckdb.org/docs

rdf4j.org/documentation

Developer

relex.ru

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

Q2WEB GmbH

Initial release

2018

1990

2004

2009

Current release

1.0.0, June 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++

C and C++

Java

Server operating systems

server-less

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
OS X
Unix
Windows

Android
Linux
Windows

Data scheme

yes

RDF Schemas

yes

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

SQL

Support of SQL

yes

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

Source-replica replication

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

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More resources

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