DBMS > Apache Pinot vs. EventStoreDB vs. RDF4J

System Properties Comparison Apache Pinot vs. EventStoreDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Primary database model

Relational DBMS

Event Store

RDF store

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

pinot.apache.org

www.eventstore.com

rdf4j.org

Technical documentation

docs.pinot.apache.org

developers.eventstore.com

rdf4j.org/documentation

Developer

Apache Software Foundation and contributors

Event Store Limited

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

Initial release

2015

2012

2004

Current release

1.0.0, September 2023

21.2, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java JDK11 or higher

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Go
Java
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

User concepts

Access control

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