DBMS > ClickHouse vs. Derby vs. Hawkular Metrics vs. Qdrant vs. RDFox

System Properties Comparison ClickHouse vs. Derby vs. Hawkular Metrics vs. Qdrant vs. RDFox

Editorial information provided by DB-Engines

Name

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

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

High performance knowledge graph and semantic reasoning engine

Primary database model

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Website

clickhouse.com

db.apache.org/derby

www.hawkular.org

github.com/qdrant/qdrant
qdrant.tech

www.oxfordsemantic.tech

Technical documentation

clickhouse.com/docs

db.apache.org/derby/manuals/index.html

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

qdrant.tech/documentation

docs.oxfordsemantic.tech

Developer

Clickhouse Inc.

Apache Software Foundation

Community supported by Red Hat

Qdrant

Oxford Semantic Technologies

Initial release

2016

1997

2014

2021

2017

Current release

v24.4.1.2088-stable, May 2024

10.17.1.0, November 2023

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java

Rust

C++

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
OS X
Windows

Docker
Linux
macOS
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

RDF schemas

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC

HTTP REST

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

RESTful HTTP API
SPARQL 1.1

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

Java

Go
Java
Python
Ruby

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

C
Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication

selectable replication factor

based on Cassandra

Collection-level replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency, tunable consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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 and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

Key-based authentication

Roles, resources, and access types

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