DBMS > ClickHouse vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. TerminusDB

System Properties Comparison ClickHouse vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. TerminusDB

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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.

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Graph DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

Document store
RDF store

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

clickhouse.com

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

terminusdb.com

Technical documentation

clickhouse.com/docs

learn.microsoft.com/azure/cosmos-db

terminusdb.github.io/terminusdb/#

Developer

Clickhouse Inc.

Microsoft

DataChemist Ltd.

Initial release

2016

2014

2012

2018

Current release

v24.4.1.2088-stable, May 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL V3

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.

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.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

Prolog, Rust

Server operating systems

FreeBSD
Linux
macOS

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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.

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

Role-based access control

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