DBMS > ClickHouse vs. FatDB vs. InfluxDB vs. Postgres-XL vs. PouchDB

System Properties Comparison ClickHouse vs. FatDB vs. InfluxDB vs. Postgres-XL vs. PouchDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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 .NET NoSQL DBMS that can integrate with and extend SQL Server.

DBMS for storing time series, events and metrics

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Time Series DBMS

Spatial DBMS

with GEO package

Document store
Spatial DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

clickhouse.com

www.influxdata.com/products/influxdb-overview

www.postgres-xl.org

pouchdb.com

Technical documentation

clickhouse.com/docs

docs.influxdata.com/influxdb

www.postgres-xl.org/documentation

pouchdb.com/guides

Developer

Clickhouse Inc.

FatCloud

Apache Software Foundation

Initial release

2016

2012

2013

2014

since 2012, originally named StormDB

2012

Current release

v24.4.1.2088-stable, May 2024

2.7.6, April 2024

10 R1, October 2018

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

Mozilla public license

Open Source

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.

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.
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.

Implementation language

C++

JavaScript

Server operating systems

FreeBSD
Linux
macOS

Windows

Linux
OS X

through Homebrew

Linux
macOS

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

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

XML type, but no XML query functionality

Secondary indexes

yes

via views

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Via inetgration in SQL Server

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

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

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API
JSON over UDP

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

only for PouchDB Server
JavaScript API

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
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

yes

via applications

user defined functions

View functions in JavaScript

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

in enterprise version only

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

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

in enterprise version only

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

Depending on used storage engine

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.

Can implement custom security layer via applications

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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