DBMS > Apache Doris vs. Elasticsearch vs. RDF4J

System Properties Comparison Apache Doris vs. Elasticsearch vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Primary database model

Relational DBMS

Search engine

RDF store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.69
Rank	#237	Overall
	#108	Relational DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

doris.apache.org
github.com/apache/doris

www.elastic.co/elasticsearch

rdf4j.org

Technical documentation

github.com/apache/doris/wiki

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

rdf4j.org/documentation

Developer

Apache Software Foundation, originally contributed from Baidu

Elastic

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

Initial release

2017

2010

2004

Current release

1.2.2, February 2023

8.6, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Elastic License

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

Linux

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

RDF Schemas

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
MySQL client

Java API
RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Memcached and Redis integration

User concepts

Access control

fine grained access rights according to SQL-standard

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Recent citations in the news

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

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28 November 2023, KDnuggets

LLM-Powered OLAP: the Tencent Experience with Apache Doris
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24 June 2022, InfoWorld

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1 September 2023, KDnuggets

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