DBMS > 4D vs. ClickHouse vs. Oracle Berkeley DB vs. RDFox vs. TimesTen

System Properties Comparison 4D vs. ClickHouse vs. Oracle Berkeley DB vs. RDFox vs. TimesTen

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.

Widely used in-process key-value store

High performance knowledge graph and semantic reasoning engine

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.4d.com

clickhouse.com

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

www.oxfordsemantic.tech

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

Technical documentation

developer.4d.com

clickhouse.com/docs

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

docs.oxfordsemantic.tech

docs.oracle.com/database/timesten-18.1

Developer

4D, Inc

Clickhouse Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oxford Semantic Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1984

2016

1994

2017

1998

Current release

v20, April 2023

v24.4.1.2088-stable, May 2024

18.1.40, May 2020

6.0, Septermber 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial license available

commercial

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.

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Implementation language

C++

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

C++

Server operating systems

OS X
Windows

FreeBSD
Linux
macOS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

RDF schemas

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

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

yes

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

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

.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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

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.

Source-replica replication

replication via a shared file system

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

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.

Roles, resources, and access types

fine grained access rights according to SQL-standard

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