DBMS > Apache Pinot vs. Hawkular Metrics vs. RDF4J vs. Transwarp StellarDB

System Properties Comparison Apache Pinot vs. Hawkular Metrics vs. RDF4J vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

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

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

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

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

pinot.apache.org

www.hawkular.org

rdf4j.org

www.transwarp.cn/en/product/stellardb

Technical documentation

docs.pinot.apache.org

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

rdf4j.org/documentation

Developer

Apache Software Foundation and contributors

Community supported by Red Hat

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

Transwarp

Initial release

2015

2014

2004

Current release

1.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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

All OS with a Java JDK11 or higher

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC

HTTP REST

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

OpenCypher

Supported programming languages

Go
Java
Python

Go
Java
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

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

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

yes

In-memory capabilities

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

User concepts

Access control

yes

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