DBMS > Hawkular Metrics vs. ITTIA vs. Qdrant vs. RDF4J

System Properties Comparison Hawkular Metrics vs. ITTIA vs. Qdrant 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.

Edge Time Series DBMS with Real-Time Stream Processing

A high-performance vector database with neural network or semantic-based matching

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

Primary database model

Time Series DBMS

Vector DBMS

RDF store

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.39
Rank	#273	Overall
	#24	Time Series DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.hawkular.org

www.ittia.com

github.com/qdrant/qdrant
qdrant.tech

rdf4j.org

Technical documentation

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

qdrant.tech/documentation

rdf4j.org/documentation

Developer

Community supported by Red Hat

ITTIA L.L.C.

Qdrant

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

Initial release

2014

2007

2021

2004

Current release

8.7

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Rust

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

Docker
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

Fixed schema

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

Numbers, Strings, Geo, 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

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

JDBC
ODBC
RESTful HTTP API
WebSocket

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

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

C
C++
JavaScript (Node.js)
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

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

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Collection-level replication

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, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

Database file passwords

Key-based authentication

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