DBMS > 4D vs. BigObject vs. ClickHouse vs. EXASOL vs. SwayDB

System Properties Comparison 4D vs. BigObject vs. ClickHouse vs. EXASOL vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Analytic DBMS for real-time computations and queries

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.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

Technical documentation

developer.4d.com

docs.bigobject.io

clickhouse.com/docs

www.exasol.com/resources

Developer

4D, Inc

BigObject, Inc.

Clickhouse Inc.

Exasol

Simer Plaha

Initial release

1984

2015

2016

2000

2018

Current release

v20, April 2023

v24.4.1.2088-stable, May 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

Open Source

GNU Affero GPL V3.0

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++

Scala

Server operating systems

OS X
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
macOS

Data scheme

yes

schema-free

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

SQL-like DML and DDL statements

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

fluentd
ODBC
RESTful HTTP API

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

.Net
JDBC
ODBC
WebSocket

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

Java
Lua
Python
R

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Lua

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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.

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.