DBMS > Hawkular Metrics vs. Oracle Coherence vs. Pinecone vs. RDF4J

System Properties Comparison Hawkular Metrics vs. Oracle Coherence vs. Pinecone vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Oracles in-memory data grid solution

A managed, cloud-native vector database

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

Primary database model

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

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

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.hawkular.org

www.oracle.com/java/coherence

www.pinecone.io

rdf4j.org

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

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

docs.pinecone.io/docs/overview

rdf4j.org/documentation

Developer

Community supported by Red Hat

Oracle

Pinecone Systems, Inc

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

Initial release

2014

2007

2019

2004

Current release

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

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
Windows

All OS with a Java VM

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

APIs and other access methods

HTTP REST

JCache
JPA
RESTful HTTP API

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Go
Java
Python
Ruby

.Net
C++
Java

Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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.

yes

User concepts

Access control

authentification to access the cache via certificates or http basic authentication

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