DBMS > ClickHouse vs. InterSystems IRIS vs. PouchDB vs. SQream DB

System Properties Comparison ClickHouse vs. InterSystems IRIS vs. PouchDB vs. SQream DB

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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.

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

JavaScript DBMS with an API inspired by CouchDB

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Document store

Relational DBMS

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	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

clickhouse.com

www.intersystems.com/products/intersystems-iris

pouchdb.com

sqream.com

Technical documentation

clickhouse.com/docs

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

pouchdb.com/guides

docs.sqream.com

Developer

Clickhouse Inc.

InterSystems

Apache Software Foundation

SQream Technologies

Initial release

2016

2018

2012

2017

Current release

v24.3.2.23-lts, April 2024

2023.3, June 2023

7.1.1, June 2019

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

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.

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++

JavaScript

C++, CUDA, Haskell, Java, Scala

Server operating systems

FreeBSD
Linux
macOS

AIX
Linux
macOS
Ubuntu
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Data scheme

yes

depending on used data model

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

via views

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
ODBC
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

.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
Rust
Scala

3rd party library

.Net
C++
Java
JavaScript (Node.js)
Python

JavaScript

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal and vertical partitioning

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

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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 IndexedDB, WebSQL or LevelDB as backend

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.

yes

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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