DBMS > ClickHouse vs. Hawkular Metrics vs. Quasardb vs. TimesTen vs. Tkrzw

System Properties Comparison ClickHouse vs. Hawkular Metrics vs. Quasardb vs. TimesTen vs. Tkrzw

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.

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

Distributed, high-performance timeseries database

In-Memory RDBMS compatible to Oracle

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

clickhouse.com

www.hawkular.org

quasar.ai

www.oracle.com/database/technologies/related/timesten.html

dbmx.net/tkrzw

Technical documentation

clickhouse.com/docs

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

doc.quasar.ai/master

docs.oracle.com/database/timesten-18.1

Developer

Clickhouse Inc.

Community supported by Red Hat

quasardb

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Mikio Hirabayashi

Initial release

2016

2014

2009

1998

2020

Current release

v24.4.1.2088-stable, May 2024

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

Open Source

Apache Version 2.0

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Windows

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

yes

APIs and other access methods

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

HTTP REST

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

Go
Java
Python
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C++
Java
PL/SQL

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

based on Cassandra

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

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

by using LevelDB

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

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

yes

Transient mode

yes

using specific database classes

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.

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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