DBMS > Hive vs. Oracle Coherence vs. RDF4J vs. SwayDB

System Properties Comparison Hive vs. Oracle Coherence vs. RDF4J vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Oracles in-memory data grid solution

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Website

hive.apache.org

www.oracle.com/java/coherence

rdf4j.org

swaydb.simer.au

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

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

rdf4j.org/documentation

Developer

Apache Software Foundation

initially developed by Facebook

Oracle

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

Simer Plaha

Initial release

2012

2007

2004

2018

Current release

3.1.3, April 2022

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Server operating systems

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
Thrift

JCache
JPA
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++
Java
PHP
Python

.Net
C++
Java

Java
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID

Isolation support depends on the API used

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

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

Access rights for users, groups and roles

authentification to access the cache via certificates or http basic authentication

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