DBMS > ClickHouse vs. Hazelcast vs. IBM Db2 vs. Microsoft Azure SQL Database

System Properties Comparison ClickHouse vs. Hazelcast vs. IBM Db2 vs. Microsoft Azure SQL Database

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Editorial information provided by DB-Engines

Name

Description

Column-oriented Relational DBMS powering Yandex

A widely adopted in-memory data grid

Common in IBM host environments, 2 different versions for host and Windows/Linux

Database as a Service offering with high compatibility to Microsoft SQL Server

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
RDF store

in DB2 LUW (Linux, Unix, Windows)

Document store
Graph DBMS

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

Score	7.61
Rank	#54	Overall
	#31	Relational DBMS

Score	8.77
Rank	#48	Overall
	#5	Key-value stores

Score	157.17
Rank	#6	Overall
	#5	Relational DBMS

Score	71.36
Rank	#15	Overall
	#10	Relational DBMS

Website

clickhouse.tech

hazelcast.com

www.ibm.com/analytics/db2

azure.microsoft.com/en-us/services/sql-database

Technical documentation

clickhouse.tech/docs

hazelcast.org/imdg/docs

www.ibm.com/support/knowledgecenter/SSEPGG

docs.microsoft.com/en-us/azure/azure-sql

Developer

Yandex LLC

Hazelcast

IBM

Microsoft

Initial release

2016

2008

1983

host version

2010

Current release

v20.11.3.3-stable, November 2020

4.1.1, December 2020

12.1, October 2016

V12

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

free version is available

commercial

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

C++

Java

C and C++

C++

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

Data scheme

yes

schema-free

yes

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.

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL

SQL-like query language

yes

APIs and other access methods

HTTP REST
JDBC
ODBC
Proprietary protocol

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC

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
Scala

3rd party library

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Transact SQL

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes

with separate tools (MQ, InfoSphere)

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

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

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Hazelcast is an in-memory computing platform that runs applications with extremely...
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Competitive advantages

Hazelcast has an optimized, multi-threaded architecture that enables the highest...
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Typical application scenarios

Hazelcast powers many types of large-scale, data processing applications. A sample...
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Key customers

Hazelcast customers include 50 of the world’s largest financial services companies,...
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Licensing and pricing models

Hazelcast provides both open source and commercial software. The open source offering...
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