DBMS > Apache Druid vs. Oracle Coherence vs. RDF4J vs. Vitess

System Properties Comparison Apache Druid vs. Oracle Coherence vs. RDF4J vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Oracles in-memory data grid solution

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

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

druid.apache.org

www.oracle.com/java/coherence

rdf4j.org

vitess.io

Technical documentation

druid.apache.org/docs/latest/design

docs.oracle.com/en/middleware/standalone/coherence

rdf4j.org/documentation

vitess.io/docs

Developer

Apache Software Foundation and contributors

Oracle

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

The Linux Foundation, PlanetScale

Initial release

2012

2007

2004

2013

Current release

29.0.1, April 2024

14.1, August 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0, commercial licenses available

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

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

yes

schema-less columns are supported

schema-free

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

SQL for querying

yes

with proprietary extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JCache
JPA
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C++
Java

Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes, with selectable consistency level

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

configurable

ACID

Isolation support depends on the API used

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

optionally

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

authentification to access the cache via certificates or http basic authentication

Users with fine-grained authorization concept

no user groups or roles

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