DBMS > Amazon Redshift vs. ClickHouse vs. Cloudflare Workers KV vs. FoundationDB

System Properties Comparison Amazon Redshift vs. ClickHouse vs. Cloudflare Workers KV vs. FoundationDB

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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 global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Ordered key-value store. Core features are complimented by layers.

Primary database model

Relational DBMS

Key-value store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Secondary database models

Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Website

aws.amazon.com/redshift

clickhouse.com

www.cloudflare.com/developer-platform/workers-kv

github.com/apple/foundationdb

Technical documentation

docs.aws.amazon.com/redshift

clickhouse.com/docs

developers.cloudflare.com/kv/api

apple.github.io/foundationdb

Developer

Amazon (based on PostgreSQL)

Clickhouse Inc.

Cloudflare

FoundationDB

Initial release

2012

2016

2018

2013

Current release

v24.4.1.2088-stable, May 2024

6.2.28, November 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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.

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++

Server operating systems

hosted

FreeBSD
Linux
macOS

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

some layers support schemas

Typing

predefined data types such as float or date

yes

some layers support typing

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Close to ANSI SQL (SQL/JSON + extensions)

supported in specific SQL layer only

APIs and other access methods

JDBC
ODBC

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

HTTP REST
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Server-side scripts

Stored procedures

user defined functions

in Python

yes

in SQL-layer only

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Linearizable consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

in SQL-layer only

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

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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.

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