DBMS > 4D vs. ClickHouse vs. Cloudflare Workers KV vs. Datomic

System Properties Comparison 4D vs. ClickHouse vs. Cloudflare Workers KV vs. Datomic

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Website

www.4d.com

clickhouse.com

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

www.datomic.com

Technical documentation

developer.4d.com

clickhouse.com/docs

developers.cloudflare.com/kv/api

docs.datomic.com

Developer

4D, Inc

Clickhouse Inc.

Cloudflare

Cognitect

Initial release

1984

2016

2018

2012

Current release

v20, April 2023

v24.4.2.141-stable, June 2024

1.0.7075, December 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

limited edition free

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.

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++

Java, Clojure

Server operating systems

OS X
Windows

FreeBSD
Linux
macOS

hosted

All OS with a Java VM

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

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

HTTP REST
Proprietary protocol

RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

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

Clojure
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

none

But extensive use of caching in the application peers

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

yes

none

But extensive use of caching in the application peers

MapReduce

Offers an API for user-defined Map/Reduce methods

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

Users and groups

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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