DBMS > 4D vs. ClickHouse vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. STSdb

System Properties Comparison 4D vs. ClickHouse vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. STSdb

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.

Microsofts flagship relational DBMS

Widely used in-process key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial 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	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.4d.com

clickhouse.com

www.microsoft.com/en-us/sql-server

www.oracle.com/database/technologies/related/berkeleydb.html

github.com/STSSoft/STSdb4

Technical documentation

developer.4d.com

clickhouse.com/docs

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/cd/E17076_05/html/index.html

Developer

4D, Inc

Clickhouse Inc.

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

STS Soft SC

Initial release

1984

2016

1989

1994

2011

Current release

v20, April 2023

v24.4.1.2088-stable, May 2024

SQL Server 2022, November 2022

18.1.40, May 2020

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

commercial license available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

OS X
Windows

FreeBSD
Linux
macOS

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL interfaced based on SQLite is available

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client 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++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C#
Java

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

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, but depending on the SQL-Server Edition

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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.

fine grained access rights according to SQL-standard

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